| People |
This Week |
Next Week |
Task Tracking (DeadLine)
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| Dong Wang
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| Lantian Li
|
- 2nd round AI Book Check – High School Edition (2/4).
- MoE project matters.
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| Ying Shi
|
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| 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
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| Junming Yuan
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| Xiaolou Li
|
- Refine RP and other application materials
- Meet and talk with some people
|
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| Zehua Liu
|
- interview
- writing code of VLLM Iterative Decode
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| 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.
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| Tianhao Wang
|
- ChainSep paper (Chinese version is almost done)
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| Xiaoxue Luo
|
- attractor-based speech separation:2-mix training
- 40% overlap rate: sisdr = 8.024
- random overlap rate: sisdr = 9.519
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| Junhui Chen
|
- had a fever, rest for a while
- come back today
- discuss with @ZhangYu
- HUAWEI gradio demo (2/5)
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| Jiaying Wang
|
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| Yu Zhang
|
- GPU Util [1]
- 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.
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| Wenqiang Du
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| Yang Wei
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| Yue Gu
|
- go back to Harbin
- write the Phd Thesis
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| Lily
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- AIGE Annual Forum
- Journal paper submission
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| Bochao Hu
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