cslt Wiki - 用户贡献 [zh-cn]

2026-03-30

2026-03-30T11:02:17Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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* AI book University version (1/2)
* English slides cleaning up
* Material preparation for 5.11 world digitial education conference
* Several meetings

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|Lantian Li
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*
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|Wenqiang Du
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* Complete test Qwen3-omni model
* Trip to Pingyao
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|Yang Wei
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* Data cleaning of concert songs
* Trip to Pingyao
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|Ying Shi
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* Revise my thesis (almost done)
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*
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*
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|Yue Gu
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* write my Phd thesis, reivew some papers
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*
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*
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|Lily
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* Journal paper final version submitted
* Material preparation for 5.11 conference
* AIGE2026 conference related tasks
* AIGE Lecturer system testing ，ready for released
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*
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*
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|Pengqi Li
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* finished paper draft.
* Traveled to Taiyuan to physical examination(again and pass).
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|Junming Yuan
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* MT-HuBERT Journal paper EN(done)
* ICASSP PPT refinement(done)
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|Yu Zhang
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* Single Node Behavior experiments append, Currently running Chain level Best Order optimize (final experiment)
* Refactored the overall narrative structure of the paper.
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|Junhui Chen
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*
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|Xiaoxue Luo
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* test the performance of USS with TDA(transformer decoder-based attractor)
** USS-EDA: 2mix_sdri=8.501, 3mix_sdri=7.372
** USS-TDA: 2mix_sdri=9.616, 3mix_sdri=8.603
* prepare some test and analysis
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*
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|Bochao Hu
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* Gongan vts: stoi has improved by using e2e vts model, continue to filter test dataset
* read papers
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|Hongcheng Zhang
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*reproduce Dynamic Acoustic Mixer（40%）&email for the author
*inhome data test for qwen3-omni on AED perform not good，shifting a proper way to eval it
*prepare paper share
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*
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|Weiman Sun
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* Preparing for the Mid-term report of My Graduation Project:
** Writing the Mid-term Report
** Making adjustments based on the project proposal
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*
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|Ge Gao
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*Download concert data for speech separation
*focus on my graduation project
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|Shuailong Li
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* Writing the Mid-term Report
*Complete the mid-term defense
*Write a technical report on edge-side models
*finished reviewing the code.
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*
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*
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2026-03-23

2026-03-23T10:56:53Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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* AIGE book (University version 1/4)
* Keep on NMI paper proof editing

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*
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|Lantian Li
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* MoE daily work
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*
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|Wenqiang Du
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*AIbabel
** Deployment funasr-nano
** find the reason for the low KWS ACC(current threshold setting strategy is wrong）
**Local deployment the Qwen3 and Testing Qwen's audio-video understanding capabilities（90%）
* Audio separation
** add causal convolution (80/100 epoch)
** add slft-attention (50/100 epoch)
* AIGE
** AI 100 question (60/100)
** High school AI couse done（14/14）
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*
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|Yang Wei
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* Audio separation stream inference. (sliding window; in progress)[https://z1et6d3xtb.feishu.cn/docx/MUdRd9v0AoenS8xgRrtcR67qnCe]
* Support MDPI rebuttal.
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|Ying Shi
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* Revise my thesis according to Prof. Han's suggestions.
* Learn some new skills for my future job
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|Yue Gu
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* write my thesis
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*
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*
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|Lily
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* Revise thesis
* Journal paper rebuttal
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*
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|Pengqi Li
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* Compiled the existing experimental results into a full paper draft.
* Traveled to Taiyuan to attend the interview and take the required physical examination.
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|Junming Yuan
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* Preparing the materials for attending ICASSP 2026 (40%)
* ICASSP Oral PPT (done)
* MT-HuBERT Journal paper refinement(5/6)
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*
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|Yu Zhang
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* GPU Util [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* Iterative chain-based LLM experiments:
** PKS steadily decreases as useful information accumulates (reflecting reduced uncertainty)
** When no new useful information is introduced, increasing the number of reasoning iterations alone no longer reduces PKS.
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|Junhui Chen
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* Reorganized the narrative structure and identified additional experiments to include （objectives and design of the Chain structure and Single Node settings）
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|Jiaying Wang
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*
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|Xiaoxue Luo
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* USS with TDA(transformer decoder-based attractor)
** write code and train the model(in training)
* prepare my resume for Huawei internship
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|Bochao Hu
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* GongAn vts
** problem: stoi is difficult to satisfy and test dataset size they want is too large.
** result: cnvsrc-multi is added to train vts, stoi metric becomes better, but it's not good enough.
** solution: more data is used to train vts(CN-CVS+CN-CVS2-P1+CN-CV3)
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|Hongcheng Zhang
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*reproduce the TAC（Timestamped Audio Captioning）'s Dynamic Acoustic Mixer（30%）
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|Weiman Sun
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* read the paper shared by hongcheng
* fine-tune the mutli-talker llm
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|Ge Gao
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*convert the MTASS framework to a streaming architecture
*prepare my graduation project
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*
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2026-03-16

2026-03-16T10:53:24Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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* NMI micromagnetic paper, reformulate theoretical foundation and rewrite the paper.
* AIGE PPT (English version) check, high-school part done.

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|Lantian Li
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* MoE daily work
* Examine master's theses
* Write NSFC proposal
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|Wenqiang Du
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* New project collaboration
* Some AI course reviews
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|Yang Wei
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* Deal with streaming audio visual speech separation.
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|Ying Shi
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*
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|Yue Gu
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* still write my Phd paper
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*
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|Lily
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* Thesis Writing
* CMT System Setup for AIGE 2026
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|Pengqi Li
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* Interview preparation
* Experimentation[https://z1et6d3xtb.feishu.cn/docx/U2ahdnEdbolPluxExxWcnmI3nog]
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|Junming Yuan
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|Yu Zhang
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* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* LLM: Swarm Lazy & Adv complex topo pruning finish (ECS for Adv Agents, PKS for Lazy Agents)
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|Junhui Chen
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* Organizing existing experiments and structuring the logic; identified some issues in the experiments and arguments (currently a bit messy) and continuing to refine.
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|Jiaying Wang
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* Thesis modifying
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|Xiaoxue Luo
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* USS with EDA(encoder-decoder based attractor)
** train the model with filtered data, test result:2mix_sdri=8.474, 3mix_sdri=7.472(The test results are the same as those of SJTU）
* Huawei project
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|Bochao Hu
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* finetuning visual encoder in new domain, which cer is 0.2727
* baseline: VSR-pre-trained Encoder + Qwen_VL finetune only (VL-Decoder) is in training
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|Hongcheng Zhang
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|Weiman Sun
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|Ge Gao
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2026-03-09

2026-03-09T10:56:44Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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* Keep on two NMI papers

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*
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*
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|Lantian Li
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*
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*
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*
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|Wenqiang Du
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* Online KWS Model Debug for AIbabel
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*
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*
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|Yang Wei
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* Developing Audio visual speech separation streaming demo.
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|Ying Shi
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* thesis
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*
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*
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|Yue Gu
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*
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*
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*
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|Lily
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* Thesis writing
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*
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*
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|Pengqi Li
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*
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*
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*
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|Junming Yuan
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*
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*
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*
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|Yu Zhang
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* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* LLM: Still Tuning the complex topo loss design (to prune Lazy Agents), find some bugs in loss design with @chenjunhui
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*
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*
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|Junhui Chen
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* LLM
** check @ZhangYu's code and debug
** design a game to prove best swarm construction has highest parameter knowledge score (can be used in RL)
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|Jiaying Wang
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* Thesis modifying
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|Xiaoxue Luo
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* attractor-based USS
** filter out a purer dataset for training(use a SED model to detect the anchor segment in audio clip that is most likely contain a sound event)
* Huawei project
** train the model using VGGSound and data provided by Huawei(in training)
*** 30epoch & 2mix: speech_sisdr = 11.785，music_sisdr = 11.7161. The previous training did have an overfitting problem.
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|Bochao Hu
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* CNVSRC.topics dataset pipeline completed and process 1000 data samples for training and testing
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|Hongcheng Zhang
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*Evaluating the boundaries of visual capabilities for small and medium-sized models in Qwen3.5
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|Weiman Sun
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* papers about the representation analysis to multi-task and instruction-tune
* add the prompt-aware lora module to the MTLLM
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*
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2026-03-02

2026-03-02T10:52:08Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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* AIhandbook for elderly people
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*
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*
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|Lantian Li
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* MoE daily work
* TASLP & IS26 papers
* FYT & HUAWEI project matters
* Review of ongoing work (thesis, research direction, project progress)
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*
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*
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|Wenqiang Du
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* check AI course vedio of high school（6/14）
* Translate "AI100 Questions" into English with Gaoge
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*
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*
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|Yang Wei
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* MD experiment (3 heads for 3 annotators) for Interspeech.
* Develop streaming AVSR service, in progress.
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*
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*
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|Ying Shi
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* thesis(almost finished)
* huawei project
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*
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*
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|Yue Gu
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* write the Phd thesis
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*
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*
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|Lily
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* INTERSPEECH Submission
* Thesis Writing
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*
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*
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|Pengqi Li
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* Coding for multi-label BCE fine-tuning and still training.
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*
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*
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|Junming Yuan
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*
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*
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*
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|Yu Zhang
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* GPU Util [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* Tunning Complex topo MMLU swarm with Lazy agents (almost done)
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*
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*
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|Junhui Chen
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* LLM：
** GAIA test: compare with MMLU test(more information from web, file, picture, etc). Result: metric loss still can detect more useful edges.
** Design experiments to prove metric loss can detect parameter knowledges (almost done)
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*
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*
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|Jiaying Wang
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* Thesis Writing
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*
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*
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|Xiaoxue Luo
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* write code about USS with TDA(transformer decoder-based attractor)
* organize relevant information on Huawei projects for subsequent delivery to shuailong
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*
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*
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|Bochao Hu
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* topic-based VSR-LLM:
** summarize the topic words from our dataset
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*
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*
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|Hongcheng Zhang
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*
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*
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*
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|Weiman Sun
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*improved the graduation project
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*
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*
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2026-03-02

2026-03-02T10:51:52Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

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|Dong Wang
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* AIhandbook for elderly people
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*
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*
|-

|-
|Lantian Li
||
* MoE daily work
* TASLP & IS26 papers
* FYT & HUAWEI project matters
* Review of ongoing work (thesis, research direction, project progress)
||
*
||
*
|-

|-
|Wenqiang Du
||
* check AI course vedio of high school（6/14）
* Translate "AI100 Questions" into English with Gaoge
||
*
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*
|-

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|Yang Wei
||
* MD experiment (3 heads for 3 annotators) for Interspeech.
* Develop streaming AVSR service, in progress.
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*
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*
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|-
|Ying Shi
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* thesis(almost finished)
* huawei project
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*
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*
|-

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|Yue Gu
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* write the Phd thesis
||
*
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*
|-

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|Lily
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* INTERSPEECH Submission
* Thesis Writing
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*
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*
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|Pengqi Li
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* Coding for multi-label BCE fine-tuning and still training.
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*
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*
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|Junming Yuan
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*
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*
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*
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|Yu Zhang
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* GPU Util [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* Tunning Complex topo MMLU swarm with Lazy agents (almost done)
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*
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*
|-

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|Junhui Chen
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* LLM：
** GAIA test: compare with MMLU test(more information from web, file, picture, etc). Result: metric loss still can detect more useful edges.
** Design experiments to prove metric loss can detect parameter knowledges (almost done)
||
*
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*
|-

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|Jiaying Wang
||
* Thesis Writing
||
*
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*
|-

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|Xiaoxue Luo
||
* write code about USS with TDA(transformer decoder-based attractor)
* organize relevant information on Huawei projects for subsequent delivery to shuailong
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*
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*
|-

|-
|Bochao Hu
||
* topic-based VSR-LLM
** summarize the topic words from our dataset
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*
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*
|-

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|Hongcheng Zhang
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*
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*
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*
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|Weiman Sun
||
*improved the graduation project
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*
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*
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2026-02-02

2026-02-02T10:38:34Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
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|Dong Wang
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*
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*
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*
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|Lantian Li
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*
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*
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*
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|Wenqiang Du
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*
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*
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*
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|Yang Wei
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*
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*
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*
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|Ying Shi
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*
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*
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*
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|Yue Gu
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* write my Phd thesis and collect the picture
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*
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*
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|Lily
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* Organized course materials production （小初高分册+ Middle school English version）
* Participated in reviewing the AI handbooks
* AIGE 2026 meeting-related tasks
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*
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*
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|Pengqi Li
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* Currently teaching at the AI Winter Camp. I will be fully back to my research in Friday.
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*
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*
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|Junming Yuan
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* checking EN middle school AI handbook(M5-M7)
* learn-not-to-listen MT-HuBERT:
** setting a threshold can improve performance on clean-speech tasks(ASR, MT-HuBERT:9.22 --> LNTL-MT-HuBERT: 8.43)
** there is some performance degradation on mixed-speech tasks(SD, MT-HuBERT:3.93 --> LNTL-MT-HuBERT: 4.31).
* draft of the journal paper(almost done)
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*
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*
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|Yu Zhang
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* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh?from=from_copylink]
* LLM: Finish complex topo code writing, and build swarm with copying node inside it (experiment still running)
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*
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*
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|Junhui Chen
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*
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*
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*
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|Jiaying Wang
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* spk order experiment finished, 4mix result are under test.
* loudness & content order verification done.
* spk order verification code preparing(2/3).
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*
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*
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|Xiaoxue Luo
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* 2-5mix multi_head separation model for Huawei project
** Modifications：
*** remove data that the mixed audio equals the target audio
*** add sing data to the speech category
*** add MSE_loss to the original SISDR_loss to control the energy amplitude of output audio
** Result: compared to the previous model, the performance is even worse
** Reasons：
*** add sing data to the speech branch is not feasible
*** there are some issues with the istft function in the original paper code
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*
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*
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|Bochao Hu
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* stage2 P2S: finetune with NLLB model using syn data, result is nearly same as before
* read papers
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*
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*
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|Hongcheng Zhang
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*prepare for weekly report
*read some new paper
*enrich my train data
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*
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*
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|Weiman Sun
||
* relevant papers
* hook the first token after the prompt to observe the model's understanding of the task at different depths.
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*
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*
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2026-01-26

2026-01-26T10:42:15Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

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|Dong Wang
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* AI middle school hand book / English version almost completed.
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*
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*
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|Lantian Li
||
* Recheck AI textbooks for senior middle school.
* MoE daily work (busy week)
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* Go on the final review of my MLA book (6/10)
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*
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|Wenqiang Du
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* Project work about AIbabel
** Upgraded online model
** New demand technology survey
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*
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*
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|Yang Wei
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*
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*
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*
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|Ying Shi
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*
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*
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*
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|Yue Gu
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* write my thesis
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*
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*
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|Lily
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*
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*
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*
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|Pengqi Li
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*
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*
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*
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|Junming Yuan
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* learn-not-to-listen MT-HuBERT
** PR(PER%), LNTL-MT-HuBERT: 7.24%, Clean-HuBERT: 5.41%, WavLM: 4.84%
** ASR(WER%), LNTL-MT-HuBERT: 8.43%, Clean-HuBERT: 6.42%, WavLM: 6.21%
** SD(DER%), LNTL-MT-HuBERT: 4.31%, Cocktail-HuBERT: 4.07%, MT-HuBERT: 3.93%
* revise ICASSP final paper
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*
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*
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|Yu Zhang
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* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* LLM
** Completed the code for Swarm MMLU metric-based optimization together with @chenjunhui
** Still working on modifying the Swarm topology code (for more complex swarm topology)
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*
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*
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|Junhui Chen
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* (caught a cold)
* MMLU
** difference in the ECS distribution between good nodes and bad nodes.
** metrics loss helps select high-quality nodes and eliminate low-quality ones. [https://z1et6d3xtb.feishu.cn/wiki/WIbewlbcwihGoCkChpZcwZpEnnh?from=from_copylink]

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*
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*
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|Jiaying Wang
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*
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*
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*
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|Xiaoxue Luo
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* prepare 2mix speech separation results for ASR test
* 2-5mix multi_head separation model for Huawei project
** data: remove data that the target audio is mixed audio(input equals output, model does not learn)
** loss: add MSE_loss to the original SISDR_loss to control the energy amplitude of output audio
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*
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*
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|Bochao Hu
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* read papers
* prepare the weekly report
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*
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*
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|Hongcheng Zhang
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*
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*
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*
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|Weiman Sun
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*Ran a completely opposite ASR task on the same data
**Consistent with last week's result
*Analyze different models
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*
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*
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2026-01-19

2026-01-19T10:48:14Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

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|Dong Wang
||
* Recheck AI textbooks for primary and middle schools.
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*
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*
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|Lantian Li
||
*
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*
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*
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|Wenqiang Du
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* Statistics the accounts for three companies, our laboratory and AIGE.
* Check AI textbooks
||
*
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*
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|Yang Wei
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*
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*
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*
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|Ying Shi
||
* Thesis
* Huawei multi-talker ASR project(Mandarin 2-mix test with FunASR-Nano-800M)
** ground-truth WER 3.89%
** separated WER 12.11%
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*
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*
|-

|-
|Yue Gu
||
* write my Phd thesis
* the seminar
||
*
||
*
|-

|-
|Lily
||
* Participated in reviewing the AI handbooks (primary/middle/high school)
* Compiled course materials for the AI Handbook (Senior Edition)
||
*
||
*
|-

|-
|Pengqi Li
||
* Writing the Experiments section.
** Focus on hard-to-explain results by formulating hypotheses and conducting deeper analysis.
||
*
||
*
|-

|-
|Junming Yuan
||
* Aug-MT-HuBERT(failed)
** Continued pre-training for 600K steps. there is still no improvement observed on clean-speech tasks.
*** Aug-MT-HuBERT has more substitution errors in clean ASR adaptation.
* Incorporate a "learn-not-to-listen" mechanism into MT-HuBERT and retrain the backbone. (in progress)
** At 425K steps, PR(PER%): 8.18%, ASR(WER%): 9.32%, SD(DER%): 5.05%
* prepare the slides of the seminar
* middle school AI textbook checking(picture, table)
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* LLM
** Rewrite the graph connectivity of Swarm MMLU (the original topology does not align with our expectations).
** Add context segmentation logic to the ECS computation, so that we can trace which preceding node a given text segment originates from.
||
*
||
*
|-

|-
|Junhui Chen
||
* LLM
** Got swarm crosswords experiment with metric detection working
** Implement multi-process of LLM instances in experiments
*** p.s.: try multi-threading, fails because a single Python interpreter only initializes one CUDA context, causing resource contention between different instances.
||
*
||
*
|-

|-
|Jiaying Wang
||
*
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* 2-5mix multi_head separation model for Huawei project[https://z1et6d3xtb.feishu.cn/docx/JtLidXiOVoQUedx3h5IcQOwAnFh]
* prepare 2mix speech separation results for ASR test
||
*
||
*
|-

|-
|Bochao Hu
||
* read some papers
* refactor P2S code, using ms-swift and adding n-best seq to input.
||
*
||
*
|-

|-
|Hongcheng Zhang
||
*Complete the training of short audio descriptions for AudioSet-SL in WavCaps
**METEOR: 0.3373， ROUGE-L: 0.3121， BLEU-4 : 0.0769， CIDEr : 0.6207
||
*
||
*
|-

|-
|Weiman Sun
||
* Label audioset vedio dataset
* Analyze the representation of MT-LLM inference and review relevant literature
||
*
||
*
|-

2026-01-12

2026-01-12T10:55:23Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* Double check English version of high-scholl handbook.
* Check English version of middle-school handbook.
||
*
||
*
|-

|-
|Lantian Li
||
* Final review of my MLA book (6/10)
* MoE daily work
||
*
||
*
|-

|-
|Wenqiang Du
||

* Complete recording high school AI courses（14/14）
* Creat PPT for high school AI course (3/14)
||
*
||
*
|-

|-
|Yang Wei
||
*
||
*
||
*
|-

|-
|Ying Shi
||
* Thesis
* Some stuff about HUAWEI project
||
*
||
*
|-

|-
|Yue Gu
||
* Revise the Phd thesis structure
* Seminar. In an anonymous vote of 20 people, 75% chose to freely discuss.
||
*
||
*
|-

|-
|Lily
||
*
||
*
||
*
|-

|-
|Pengqi Li
||
* Drafting the method part of paper.
* Identified bugs in the reproduction code. Re-ran experiments and confirmed that conclusions remain consistent.
* Assisting with the revision of the middle school handbook.
||
*
||
*
|-

|-
|Junming Yuan
||
*
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
* Finish final exam
* Writing code to analyze LLM Swarm metrics, mainly looking at how ECS/PKS correlate with the optimized edge probability.
||
*
||
*
|-

|-
|Junhui Chen
||
* finish final exam
* debug code about swarm minicrossword test
||
*
||
*
|-

|-
|Xiaolou Li
||
*
||
*
||
*
|-

|-
|Jiaying Wang
||
* spk model training(130/300):reconstruct data, now training data is aligned with separation data
** recall@k of 130 epoch: 2mix recall@2=0.9799, 3mix recall@3=0.9101, 4mix recall@4=0.8247

||
*
||
*
|-

|-
|Tianhao Wang
||
* revised ChainSep paper
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* 2-5mix multi_head separation model for Huawei project
** write code for the multi-speaker and multi-sound events separation task，complete data preparation and feature extraction
** adjust the model structure to three heads(speech, music and others), the model is still in training, and current val_sisdr is 11.38
||
*
||
*
|-

|-

|Bochao Hu
||
* finish final exam
* debug and train vsr E2E model, still in training
* resently results [https://z1et6d3xtb.feishu.cn/wiki/MQS9wt7gYikboBkJ09ScovGxnmg?from=from_copylink]
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* finish final exam
* debug for asu-llm code and train the task audio caption with WavCaps(1/20 epoches)
||
*
||
*
|-

2026-01-05

2026-01-05T10:57:51Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
*
||
*
||
*
|-

|-
|Lantian Li
||
* Final review of my MLA book (3/10)
* MoE daily work
||
*
||
*
|-

|-
|Wenqiang Du
||
* Check AI course PPT(4/14)
* Completed AI100 question task and will be uploaded to the platform this month
||
*
||
*
|-

|-
|Yang Wei
||
* Some additional result analysis and some revisions on manuscript according to the reviewer' comments. [https://z1et6d3xtb.feishu.cn/docx/Woz0dFwsaoWZuOxZ2KGcm9MxnKe?from=from_copylink][https://z1et6d3xtb.feishu.cn/docx/VIZadovoZohLscxQUYNcu59HnGd?from=from_copylink]
||
*
||
*
|-

|-
|Ying Shi
||
*
||
*
||
*
|-

|-
|Pengqi Li
||
* Draft Paper: The framework and core content are complete.
* AI Handbook: Checking and verifying references.
* Winter Camp Preparation: Preparing materials for the Tsinghua University Middle School AI Winter Camp.
||
*
||
*
|-

|-
|Junming Yuan
||
* Aug-MT-HuBERT:
** Fixed the pre-training to 100K steps, compared 3 noise ratios（50%, 80%, and 100%）and 2 different SNR sampling strategies([-3, 3] uniform / [0, 10] Gauss).
*** Best setting, PR performance(PER): 8.12 -> 8.08, ASR performance(WER): 9.22 -> 9.07
*** There is still around 3% gap compared to HuBERT.
* SS adaptation(SI-SDRi):
** Cocktail-HuBERT(14.76) > MT-HuBERT(13.93) > WavLM(13.83) > ConvTasNet(10.39)
* Draft Paper( CN version almost done)
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh?from=from_copylink]
* working on the big assignment and preparing for the final exam.
||
*
||
*
|-

|-
|Junhui Chen
||
* prepare for final exam
||
*
||
*
|-

|-
|Xiaolou Li
||
* Prepared applications for 4 CDT programmes
||
*
||
*
|-

|-
|Jiaying Wang
||
* spk order separation training
||
*
||
*
|-

|-
|Tianhao Wang
||
* additional experiments for ChainSep [https://z1et6d3xtb.feishu.cn/docx/RG5Qd9ashoGhw5xc9M2cAVcHnLc]
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* 2-5mix attractor-based USS model for Huawei project
** SI-SDR : 2mix: 4.725， 3mix: 0.866， 4mix: -1.155， 5mix: -2.709
* design a better solution for Huawei project
** multi-head separation (two groups: speakers and events)
||
*
||
*
|-

|-
|Yue Gu
||
* write Phd defense slides
||
*
||
*
|-

|-
|Lily
||
*
||
*
||
*
|-

|-
|Bochao Hu
||
* P2S wer: 45%.data:20% GT 20% real seq 60% synthetic seq. llm can't correct with high per(> 30%)
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* finish the main code of ASU-LLM (CLAP + HuBERT)。The core architecture consists of a dual-stream encoder combing CLAP and Audio Hubert,integrated with LLaMA
||
*
||
*
|-

2026-01-05

2026-01-05T10:43:01Z

Hubochao：

2025-12-29

2025-12-29T10:56:21Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* All the textbook for primary and middle schools done
* English version of Middle school handbook almost done (reference needed)
||
*
||
*
|-

|-
|Lantian Li
||
* Final review of my MLA book (1/10)
* Project support for HUAWEI and FYT
* MoE daily work
||
*
||
*
|-

|-
|Ying Shi
||
* Thesis
* Huawei project
||
*
||
*
|-

|-
|Zhenghai You
||
* IRA TSE with SSL[https://z1et6d3xtb.feishu.cn/docx/S0XgdZD5bo3HK8xhnx6coPYknUf]
||
* training in noisy enroll & Improve the fusion method & Trying more SSL models
||
*
|-

|-
|Junming Yuan
||
* Aug-MT-HuBERT exp(in training)
* write journal paper(4/7)
||
*
||
*
|-

|-
|Xiaolou Li
||
*
||
*
||
*
|-

|-
|Zehua Liu
||
*Train Topic and Context Iterative Decode exp for Graduation Thesis
*Reading some paper for Intership
||
*
||
*
|-

|-
|Pengqi Li
||
*
||
*
||
*
|-

|-
|Tianhao Wang
||
* supplemental experiments for ChainSep
** ablation study for iterative separation (only use text)
** finding some better samples for visualization
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* 2-mix experiment of attractor-based SS(Done)
* 2-5mix USS model for Huawei project(in training)
||
*
||
*
|-

|-
|Junhui Chen
||
* LLM
** discuss the reversal experiment results with @ZhangYu
** code for swarm metrics analysis (needs further discussion)
* study for final exam
||
* study for final exam
||
*
|-

|-
|Jiaying Wang
||
* spk model recall@k test finished：2mix recall@2=0.9860, 3mix recall@3=0.9176, 4mix recall@4=0.8236
* prepare spk perceptual data for separation training
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh
* LLM Reverse curse:
** Direct put answer into context: High ECS, Low PKS
** Reversal logic in context: High ECS, High PKS
* study for final exam...
||
* study for final exam...
||
*
|-

|-
|Wenqiang Du
||
* Recording high school AI courses and make related ppt(10/14)
||
*
||
*
|-

|-
|Yang Wei
||
* MD fine-tune experiment on AISHELL2 + UY/CH-CHILD (cross validation) [https://z1et6d3xtb.feishu.cn/docx/Woz0dFwsaoWZuOxZ2KGcm9MxnKe?from=from_copylink]
||
*
||
*
|-

|-
|Yue Gu
||
* reading some papers about the passive acoustic monitoring（PAM）to understand the current research status and future prospects of this field.
* writing my Phd thesis
||
*
||
*
|-

|-
|Lily
||
*
||
*
||
*
|-

|-
|Bochao Hu
||
* video to phoneme per: 27%, phoneme to sentence wer: 44%
* try to explore the correct mistakes ability of llm: rebulid training data(in training)
* study for final exam
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* study for final exam
* read some papers
||
*
||
*
|-

2025-12-29

2025-12-29T10:52:04Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* All the textbook for primary and middle schools done
* English version of Middle school handbook almost done (reference needed)
||
*
||
*
|-

|-
|Lantian Li
||
* Final review of my MLA book (1/10)
* Project support for HUAWEI and FYT
* MoE daily work
||
*
||
*
|-

|-
|Ying Shi
||
* Thesis
* Huawei project
||
*
||
*
|-

|-
|Zhenghai You
||
* IRA TSE with SSL[https://z1et6d3xtb.feishu.cn/docx/S0XgdZD5bo3HK8xhnx6coPYknUf]
||
* training in noisy enroll & Improve the fusion method & Trying more SSL models
||
*
|-

|-
|Junming Yuan
||
* Aug-MT-HuBERT exp(in training)
* write journal paper(4/7)
||
*
||
*
|-

|-
|Xiaolou Li
||
*
||
*
||
*
|-

|-
|Zehua Liu
||
*Train Topic and Context Iterative Decode exp for Graduation Thesis
*Reading some paper for Intership
||
*
||
*
|-

|-
|Pengqi Li
||
*
||
*
||
*
|-

|-
|Tianhao Wang
||
* supplemental experiments for ChainSep
** ablation study for iterative separation (only use text)
** finding some better samples for visualization
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* 2-mix experiment of attractor-based SS(Done)
* 2-5mix USS model for Huawei project(in training)
||
*
||
*
|-

|-
|Junhui Chen
||
* LLM
** discuss the reversal experiment results with @ZhangYu
** code for swarm metrics analysis (needs further discussion)
* study for final exam
||
* study for final exam
||
*
|-

|-
|Jiaying Wang
||
* spk model recall@k test finished：2mix recall@2=0.9860, 3mix recall@3=0.9176, 4mix recall@4=0.8236
* prepare spk perceptual data for separation training
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh
* LLM Reverse curse:
** Direct put answer into context: High ECS, Low PKS
** Reversal logic in context: High ECS, High PKS
* study for final exam...
||
* study for final exam...
||
*
|-

|-
|Wenqiang Du
||
* Recording high school AI courses and make related ppt(10/14)
||
*
||
*
|-

|-
|Yang Wei
||
* MD fine-tune experiment on AISHELL2 + UY/CH-CHILD (cross validation) [https://z1et6d3xtb.feishu.cn/docx/Woz0dFwsaoWZuOxZ2KGcm9MxnKe?from=from_copylink]
||
*
||
*
|-

|-
|Yue Gu
||
* reading some papers about the passive acoustic monitoring（PAM）to understand the current research status and future prospects of this field.
* writing my Phd thesis
||
*
||
*
|-

|-
|Lily
||
*
||
*
||
*
|-

|-
|Bochao Hu
||
* video to phoneme per: 27%, phoneme to sentence wer: 44%
* try to explore the correct mistakes ability of llm: adding noised data(in training)
* study for final exam
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* study for final exam
* read some papers
||
*
||
*
|-

2025-12-22

2025-12-22T10:52:27Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* AI textbook high school grad-2 (6/12)
* AIGE 2025 seminar

||
*
||
*
|-

|-
|Lantian Li
||
* Complete the 2nd review of AI Book (High School).
* Go on an MoE business trip.
* Submit the Phase I proposal for the Huang Danian Project.
||
* MLA book final check.
||
*
|-

|-
|Ying Shi
||
* ICASSP rebuttal
* thesis
||
*
||
*
|-

|-
|Zhenghai You
||
* Complete the Hubert iterative adaptation Exp, and the result is slightly worse than baseline in clean enroll(~0.9). Trying to test on noisy enroll
||
*
||
*
|-

|-
|Junming Yuan
||
* ICASSP rebuttal
* MT-HuBERT exp
||
*
||
*
|-

|-
|Xiaolou Li
||
* PhD Application
||
*
||
*
|-

|-
|Zehua Liu
||
*Iterative Decoding Exp for graduation thesis
||
*
||
*
|-

|-
|Pengqi Li
||
* Quantitatively measure the reliability of 7 Saliency map methods for speaker verification. (FGGB, SSAB, Corr-RISE, SFAM, three CAMs)
**Conclusion: Corr-RISE and LayerCAM are relatively reliable methods.
||
* Start drafting the report for paper
||
*
|-

|-
|Tianhao Wang
||
* finish ChainSep paper
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* paper sharing
* 2-mix experiment of attractor-based SS
||
*
||
*
|-

|-
|Junhui Chen
||
* LLM
** merge metrics detection module into swarm pipline (done)
** check some code recently written by ZhangYu
* finished HUAWEI demo web developing
||
* write analysis code for swarm
* do homework and prepare for some final exams
||
*
|-

|-
|Jiaying Wang
||
* spk model code finished and training
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh
* LLM
** Completed the implementation and metric collection for the reversal curse experiment; results are still under analysis.
** Completed the Qwen-based metric collection implementation to support stronger base model performance.
* help @chenjunhui for Huawei gradio demo deploy

||
* Obtain some quantitative results from the Reversal Curse latent learning experiments.
* Need to work on some homework and prepare for the final exams.
||
*
|-

|-
|Wenqiang Du
||
* Rebuttal the reviewers' comments about high school AI course's draft(done)
* Some work about project
** Huawei and AIbabel
||
*
||
*
|-

|-
|Yang Wei
||
* MD experiment for SSL frontend baseline, and some other result analysis for ICCASP rebuttal.[https://z1et6d3xtb.feishu.cn/docx/QGKwdgXoIoWW40xafrTcVUcNnoh?from=from_copylink]
||
*
||
*
|-

|-
|Yue Gu
||
* write my Phd thesis
||
*
||
*
|-

|-
|Lily
||
* AIGE Annual Forum（December 19th）
* ICASSP author respond
* Thesis
||
*
||
*
|-

|-
|Bochao Hu
||
* the latest epoch's per: 33.6%, it will be a better result after training
* preparing for running a whole pipeline
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* did research for ASU-LLM tasks
||
*
||
*
|-

2025-12-22

2025-12-22T10:47:46Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* AI textbook high school grad-2 (6/12)
* AIGE 2025 seminar

||
*
||
*
|-

|-
|Lantian Li
||
* Complete the 2nd review of AI Book (High School).
* Go on an MoE business trip.
* Submit the Phase I proposal for the Huang Danian Project.
||
* MLA book final check.
||
*
|-

|-
|Ying Shi
||
* ICASSP rebuttal
* thesis
||
*
||
*
|-

|-
|Zhenghai You
||
* Complete the Hubert iterative adaptation Exp, and the result is slightly worse than baseline in clean enroll(~0.9). Trying to test on noisy enroll
||
*
||
*
|-

|-
|Junming Yuan
||
* ICASSP rebuttal
* MT-HuBERT exp
||
*
||
*
|-

|-
|Xiaolou Li
||
*
||
*
||
*
|-

|-
|Zehua Liu
||
*Iterative Decoding Exp for graduation thesis
||
*
||
*
|-

|-
|Pengqi Li
||
* Quantitatively measure the reliability of 7 Saliency map methods for speaker verification. (FGGB, SSAB, Corr-RISE, SFAM, three CAMs)
**Conclusion: Corr-RISE and LayerCAM are relatively reliable methods.
||
* Start drafting the report for paper
||
*
|-

|-
|Tianhao Wang
||
* finish ChainSep paper
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* paper sharing
* 2-mix experiment of attractor-based SS
||
*
||
*
|-

|-
|Junhui Chen
||
* LLM
** merge metrics detection module into swarm pipline (done)
** check some code recently written by ZhangYu
* finished HUAWEI demo web developing
||
* write analysis code for swarm
* do homework and prepare for some final exams
||
*
|-

|-
|Jiaying Wang
||
* spk model code finished and training
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh
* LLM
** Completed the implementation and metric collection for the reversal curse experiment; results are still under analysis.
** Completed the Qwen-based metric collection implementation to support stronger base model performance.
* help @chenjunhui for Huawei gradio demo deploy

||
* Obtain some quantitative results from the Reversal Curse latent learning experiments.
* Need to work on some homework and prepare for the final exams.
||
*
|-

|-
|Wenqiang Du
||
* Rebuttal the reviewers' comments about high school AI course's draft(done)
* Some work about project
** Huawei and AIbabel
||
*
||
*
|-

|-
|Yang Wei
||
* MD experiment for SSL frontend baseline, and some other result analysis for ICCASP rebuttal.[https://z1et6d3xtb.feishu.cn/docx/QGKwdgXoIoWW40xafrTcVUcNnoh?from=from_copylink]
||
*
||
*
|-

|-
|Yue Gu
||
* write my Phd thesis
||
*
||
*
|-

|-
|Lily
||
* AIGE Annual Forum（December 19th）
* ICASSP author respond
* Thesis
||
*
||
*
|-

|-
|Bochao Hu
||
* the latest epoch's per: 33.6%
* read papers
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* did research for ASU-LLM tasks
||
*
||
*
|-

2025-12-15

2025-12-15T10:55:17Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
*
||
*
||
*
|-

|-
|Lantian Li
||
*
||
*
||
*
|-

|-
|Ying Shi
||
* thesis
* Multi-talker ASR Demo
||
*
||
*
|-

|-
|Zhenghai You
||
* Support work for Huawei SS project (2/3/4 zh mix)
* Complete the training of base model and iterative model, and Hubert-base extractor is training
||
*
||
*
|-

|-
|Junming Yuan
||
* Current experimental progress of MT-HuBERT[https://z1et6d3xtb.feishu.cn/docx/AzyhdbCjyooVKOxLFV3cfY2MnuZ]
* MT-HuBERT paper EN v0.4(4/7)
||
*
||
*
|-

|-
|Xiaolou Li
||
* PhD Application
||
*
||
*
|-

|-
|Zehua Liu
||
*
||
*
||
*
|-

|-
|Pengqi Li
||
* Transfer CAMs methods from the classification task to speaker verification task.
||
* Qualitatively and quantitatively measure the reliability of these methods. (FGGB, SSAB, Corr-RISE, SFAM, CAMs)
||
*
|-

|-
|Tianhao Wang
||
* refine the ChainSep paper and adjust it to overleaf
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* Write code to combine SepFormer and EDA method, the model is in training
* read papers
||
*
||
*
|-

|-
|Junhui Chen
||
* HUAWEI gradio demo (4/5)
* Integrate the current metric collection code into GPTSwarm (80%)
||
*
||
*
|-

|-
|Jiaying Wang
||
* content experiments test finish
* loudness experiments testing
* spk model code preparing
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util: https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh?from=from_copylink
* LLM: Latent learning simple reverse exp code (90%, lack for metric analysis code and Oracle Retrieval Code)
||
*
||
*
|-

|-
|Wenqiang Du
||
* Rebuttal the reviewers' comments about high school AI course's draft(80%)
* Calendar done
||
*
||
*
|-

|-
|Yang Wei
||
*
||
*
||
*
|-

|-
|Yue Gu
||
* write my Phd thesis
||
*
||
*
|-

|-
|Lily
||
* Check AI handbook (初二下册，高一下册)
* AIGE Annual Forum（December 19th）
||
*
||
*
|-

|-
|Bochao Hu
||
* Phoneme to sentence
** 0% error, WER: 2.1% | 5% error, WER: 11.0% | 10% error, WER: 32.4% | 20% error, WER: 66.0% | 30% error, WER: 89.3%
* Video to Phoneme: Change the model architecture to baseline. First stage(<4s) is in training
||
*
||
*
|-

|-
|Hongcheng Zhang
||
* construct code for ASU-LLM（10%）
||
*
||
*
|-

2025-12-08

2025-12-08T11:04:01Z

Hubochao：

{| class="wikitable"
!People !! This Week !! Next Week !! Task Tracking (DeadLine)
|-

|-
|Dong Wang
||
* MD paper done
* AI handbook middel school 2 grad almost done.

||
*
||
*
|-

|-
|Lantian Li
||
* 2nd round AI Book Check – High School Edition (2/4).
* MoE project matters.
||
*
||
*
|-

|-
|Ying Shi
||
* thesis
||
*
*
||
*
|-

|-
|Zhenghai You
||
* Some support work for Huawei SS project
* Iterative Adaptation TSE：
** Complete the training framework code
** Training 16k Base model and IRA model as baselines to adapt to Hubert or WavLM
||
*
||
*
|-

|-
|Junming Yuan
||
*
||
*
||
*
|-

|-
|Xiaolou Li
||
* Refine RP and other application materials
* Meet and talk with some people
||
*
||
*
|-

|-
|Zehua Liu
||
*interview
*writing code of VLLM Iterative Decode
||
*
||
*
|-

|-
|Pengqi Li
||
* Investigate metric learning explainability methods, including those applied in speaker recognition verification tasks and other fields such as image processing.
* Transfer four metric learning explainability methods (FGGB, SSAB, Corr-RISE, SFAM) from the image field to speaker verification.
* AI course of Tsinghua University Middle School.
||
*
||
*
|-

|-
|Tianhao Wang
||
* ChainSep paper (Chinese version is almost done)
||
*
||
*
|-

|-
|Xiaoxue Luo
||
* attractor-based speech separation:2-mix training
** 40% overlap rate: sisdr = 8.024
** random overlap rate: sisdr = 9.519
||
*
||
*
|-

|-
|Junhui Chen
||
* had a fever, rest for a while
* come back today
** discuss with @ZhangYu
** HUAWEI gradio demo (2/5)
||
*
||
*
|-

|-
|Jiaying Wang
||
* recurring fevers after flu, still not fully recovered
* content experiment training finished
* loudness experiment 2mix, 3mix training finished
||
*
||
*
|-

|-
|Yu Zhang
||
* GPU Util [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh?from=from_copylink]
* LLM
** Reflection methods that provide more detailed feedback (for example, offering a full solution rather than just keywords describing the mistake) are more likely to receive higher ECS scores.
** When LLMs use Reflection feedback, ECS and PKS scores exhibit a strong negative correlation.
||
*
||
*
|-

|-
|Wenqiang Du
||
* Rebuttal the reviewers' comments about high school AI course's draft
* Calendar content preparation
* Some company matters
** New kws model update（aibabel）
** project acceptance （核二院）
||
*
||
*
|-

|-
|Yang Wei
||
* More partial fine-tune experiments for MD paper[https://z1et6d3xtb.feishu.cn/docx/Qu1yd5vdDoggfIxvGknclp0ongg?from=from_copylink]
||
*
||
*
|-

|-
|Yue Gu
||
* go back to Harbin
* write the Phd Thesis
||
*
||
*
|-

|-
|Lily
||
* AIGE Annual Forum
* Journal paper submission
||
*
||
*
|-

|-
| Bochao Hu
||
* Biweekly report
* P2S bug and result [https://z1et6d3xtb.feishu.cn/wiki/D2UpwqQ6vi8aN4kCVVmcwUeuncd]
||
*
||
*
|-