1 citations · 2 across the 8 of their papers we have counts for
8 papers
A Step Back: Prefix Importance Ratio Stabilizes Policy Optimization
Shiye Lei, Zhihao Cheng, Dacheng Tao
Reinforcement learning (RL) post-training has increasingly demonstrated strong ability to elicit reasoning behaviors in large language models (LLMs). For training efficiency, rollo…
Offline Behavioral Data Selection
Shiye Lei, Zhihao Cheng, Dacheng Tao
Behavioral cloning is a widely adopted approach for offline policy learning from expert demonstrations. However, the large scale of offline behavioral datasets often results in com…
State Diversity Matters in Offline Behavior Distillation
Shiye Lei, Zhihao Cheng, Dacheng Tao
Offline Behavior Distillation (OBD), which condenses massive offline RL data into a compact synthetic behavioral dataset, offers a promising approach for efficient policy training…
Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power
Yuzhu Chen, Tian Qin, Xinmei Tian +2
Equivariant neural networks encode the intrinsic symmetry of data as an inductive bias, which has achieved impressive performance in wide domains. However, the understanding to the…
Revisiting LLM Reasoning via Information Bottleneck
Shiye Lei, Zhihao Cheng, Kai Jia +1
Large language models (LLMs) have recently demonstrated remarkable progress in reasoning capabilities through reinforcement learning with verifiable rewards (RLVR). By leveraging s…
Offline Behavior Distillation
Shiye Lei, Sen Zhang, Dacheng Tao
Massive reinforcement learning (RL) data are typically collected to train policies offline without the need for interactions, but the large data volume can cause training inefficie…
Inverse learning of black-box aggregator for robust Nash equilibrium
Guanpu Chen, Gehui Xu, Fengxiang He +3
In this note, we investigate the robustness of Nash equilibria (NE) in multi-player aggregative games with coupling constraints. There are many algorithms for computing an NE of an…
Image Captions are Natural Prompts for Text-to-Image Models
Shiye Lei, Hao Chen, Sen Zhang +2
With the rapid development of Artificial Intelligence Generated Content (AIGC), it has become a common practice to train models on synthetic data due to data-scarcity and privacy l…