3 citations · 3 across the 5 of their papers we have counts for
5 papers
Information-Time Proximal Policy Optimization
Yongcheng Zeng, Xinyu Cui, Yan Song +9
RLVR has substantially improved the reasoning capabilities of LLMs. However, existing methods typically parameterize temporal progression in the Markov Decision Process by token-by…
Learning Stateful Predictive Knowledge From Experience
Yan Song, Xidong Feng, Bo Liu +7
As large language model (LLM) agents increasingly learn from experience, they primarily rely on trajectory-level reflection to extract insights. Viewed through the lens of predicti…
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning
Peng Yu, Cheng Deng, Beiya Dai +2
Autoregressive large language models (LLMs) pre-trained by next token prediction are inherently proficient in generative tasks. However, their performance on knowledge-driven tasks…
AceMap: Knowledge Discovery through Academic Graph
Xinbing Wang, Luoyi Fu, Xiaoying Gan +23
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering sear…
Entropy-Regularized Token-Level Policy Optimization for Language Agent Reinforcement
Muning Wen, Junwei Liao, Cheng Deng +3
Large Language Models (LLMs) have shown promise as intelligent agents in interactive decision-making tasks. Traditional approaches often depend on meticulously designed prompts, hi…