| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
|
- Check response for 16 AI textbooks
- Recheck micromagentics paper
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| Lantian Li
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| Wenqiang Du
|
- Spech separation task
- add some loss to reduce leakage problem
- Baseline evaluation for audio event tasks
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| Yang Wei
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- Train a audio separation model with larger dataset and remove speech subset with label problem
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| Ying Shi
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| Yue Gu
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- write my phd thesis and revise one chapter
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| Lily
|
- GPT image generation: covers for 16 AI textbooks + AI100 (4 themes); collected feedback for further improvement
- Reviewed Overleaf version of the 16 AI textbooks
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| Pengqi Li
|
- Continued the revision of the paper submitted to Journal of Chinese Information Processing
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| Junming Yuan
|
- journal paper refinement(done and submit)
- prepare ICASSP oral presentation(done)
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| Yu Zhang
|
- GPU Util: [1]
- Paper:
- Finish all lazy bubble prune accuracy & token consumption test
- Refine paper with @chenjunhui
- GAIA test (real word ToT MAS pipeline with function calling RAG)
- original ACC: 11 / 52
- ACC without all WebSearch: 8 / 52 (mostly are questions that can be solved by FileAnalyze or without any additional information)
- ACC without WebSearch that seg-ECS < 0.4: 11 / 52
- ACC without WebSearch that seg-ECS > 0.4: 8 / 52
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| Junhui Chen
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- still sick
- continue to refining the paper, and looking for references (80%)
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| Xiaoxue Luo
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- retrain the USS-eda model using the data and training configuration from the SJTU 's paper
- train 2-3mix USS-tda model to compare the separation results with USS-eda(in training)
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| Bochao Hu
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- confirm cvs3's plan with @xiaolou, complete all label generation, data part is done
- handover gonganbu's tech report
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| Hongcheng Zhang
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- test Qwen models and write report
- read some paper
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| Weiman Sun
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- test Qwen models and write report
- write graduation thesis
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| Ge Gao
|
- experiments on audio separation and prepared ball data
- wrote my graduation thesis
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| Shuailong Li
|
- Test on Teacher Wei's dataset
- completed my graduation project UI and wrote the corresponding documentation.
- Reproduction on the MTASS original dataset（loss：MSE+SI-SDR）
- SDRi（speech=6.95 music=4.63 others=4.50 avg=5.43）
- The perceived volume has not decreased
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