5 papers · 1 filter
Process Reward Informed Tree Rollout for Effective Multi-Turn RL
Xintong Li, Sha Li, Yuwei Zhang +8
Reinforcement learning (RL) has become a key approach for training LLM agents, yet popular methods such as GRPO/RLOO rely on multiple independently sampled complete trajectories fo…
Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection
Yuwei Zhang, Wenhao Yu, Shangbin Feng +5
Despite significant advances in large language models (LLMs), their knowledge memorization capabilities remain underexplored, due to the lack of standardized and high-quality test…
Attention Reveals More Than Tokens: Training-Free Long-Context Reasoning with Attention-guided Retrieval
Yuwei Zhang, Jayanth Srinivasa, Gaowen Liu +1
Large Language Models (LLMs) often exhibit substantially shorter effective context lengths than their claimed capacities, especially when handling complex reasoning tasks that requ…
Toward Multi-Session Personalized Conversation: A Large-Scale Dataset and Hierarchical Tree Framework for Implicit Reasoning
Xintong Li, Jalend Bantupalli, Ria Dharmani +2
There has been a surge in the use of large language models (LLM) conversational agents to generate responses based on long-term history from multiple sessions. However, existing lo…
LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory
Di Wu, Hongwei Wang, Wenhao Yu +3
Recent large language model (LLM)-driven chat assistant systems have integrated memory components to track user-assistant chat histories, enabling more accurate and personalized re…