“2026-04-13”版本间的差异

2026年4月13日 (一) 10:32的版本

People	This Week	Next Week	Task Tracking (DeadLine)
Dong Wang
Lantian Li	FgW daily work MLA book (3/4)
Wenqiang Du
Yang Wei
Ying Shi	revise my thesis
Yue Gu	write my Phd thesis
Lily
Pengqi Li	Paper Draft Completion & Revision Plan
Junming Yuan	Preparing the materials for attending ICASSP ZH paper draft (need refine)
Yu Zhang	GPU Util: [1] Chain level experiments: After introducing the Metric Reward, the weights of correct edges converge faster compared to training with pure reinforcement learning alone. The worse the situation when the Metric Reward is introduced (i.e., the lower the weights of critical edges), the more significant the difference compared to not using the Metric Reward.
Junhui Chen	To strengthen the robustness of the conclusions, conducting additional experiments: Introduce a new baseline (AgentPrune). Add experiments on a new dataset (GSM8K). Reproduce the results on other LLM base models. Paper writing
Jiaying Wang
Bochao Hu
Hongcheng Zhang
Weiman Sun
Ge Gao	reproduce spatialnet for speech separation
Shuailong Li	read some papers USE（Sepformer and BSRNN and TDN）

@@ 第107行： / 第107行： @@
 |Yu Zhang
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+* GPU Util: [https://z1et6d3xtb.feishu.cn/wiki/XX4NwX3tJiBDcgkMi0hcFUtInHh]
+* Chain level experiments:
+** After introducing the Metric Reward, the weights of correct edges converge faster compared to training with pure reinforcement learning alone.
+** The worse the situation when the Metric Reward is introduced (i.e., the lower the weights of critical edges), the more significant the difference compared to not using the Metric Reward.
 ||
 *
@@ 第118行： / 第121行： @@
 |Junhui Chen
 ||
-*
+* To strengthen the robustness of the conclusions, conducting additional experiments:
+** Introduce a new baseline (AgentPrune).
+** Add experiments on a new dataset (GSM8K).
+** Reproduce the results on other LLM base models.
+* Paper writing
 ||
 *