5 papers
Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs
Xuyuan Liu, Shengyu Chen, Xinshuai Dong +6
Large language models (LLMs) often produce incorrect or outdated content after being employed. Efficient and accurate knowledge updates without costly retraining are a major challe…
MIITA: Memory-Induced Inference-Time Adaptation for Continual Learning with Small Language Models
Dong Li, Yanchi Liu, Xujiang Zhao +6
Continual learning (CL) is essential for small language models (SLMs) to adapt to evolving real-world needs in resource-constrained deployments. However, directly updating their li…
DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router
Minghao Guo, Qingcheng Zeng, Xujiang Zhao +5
Large Language Models (LLMs) excel at many reasoning tasks but struggle with knowledge-intensive queries due to their inability to dynamically access up-to-date or domain-specific…
SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
Peng Xia, Jianwen Chen, Hanyang Wang +10
Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past experiences. Existing memory-based m…
Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement
Wangyang Ying, Yanchi Liu, Xujiang Zhao +5
Automatically extracting workflows as procedural graphs from natural language is promising yet underexplored, demanding both structural validity and logical alignment. While recent…