256 citations · 305 across the 20 of their papers we have counts for
6 papers · 1 filter
AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress
Zhiheng Xi, Chenyang Liao, Guanyu Li +12
Despite rapid development, large language models (LLMs) still encounter challenges in multi-turn decision-making tasks (i.e., agent tasks) like web shopping and browser navigation,…
Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning
Senjie Jin, Lu Chen, Zhiheng Xi +9
Natural language chain-of-thought (N-CoT) and Program chain-of-thought (P-CoT) have emerged as two primary paradigms for large language models (LLMs) to solve mathematical reasonin…
Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination
Mingqi Wu, Zhihao Zhang, Qiaole Dong +11
Reasoning in large language models has long been a central research focus, and recent studies employing reinforcement learning (RL) have introduced diverse methods that yield subst…
Why Reinforcement Fine-Tuning Enables MLLMs Preserve Prior Knowledge Better: A Data Perspective
Zhihao Zhang, Qiaole Dong, Qi Zhang +12
Post-training algorithms such as Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT) are widely used to adapt (multimodal) large language models to downstream tasks. W…
What Makes a Good Speech Tokenizer for LLM-Centric Speech Generation? A Systematic Study
Xiaoran Fan, Zhichao Sun, Yangfan Gao +19
Speech-language models (SLMs) offer a promising path toward unifying speech and text understanding and generation. However, challenges remain in achieving effective cross-modal ali…
EliteKV: Scalable KV Cache Compression via RoPE Frequency Selection and Joint Low-Rank Projection
Yuhao Zhou, Sirui Song, Boyang Liu +6
Rotary Position Embedding (RoPE) enables each attention head to capture multi-frequency information along the sequence dimension and is widely applied in foundation models. However…