4 papers
ConvMem: Convolutional Memory for Long-Context Reasoning
Hongming Zhang, Zhaozhen Gu, Fengshuo Bai +6
While Large Language Models (LLMs) have demonstrated impressive capabilities, they often struggle with extremely long contexts due to fixed context limits. To address this, sequent…
HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation
XinQi Wang, Jinwei Xiao, Sijia Cui +4
Large language model (LLM) agents often perform poorly on complex, long-horizon tasks because their context becomes increasingly cluttered over time. As interactions accumulate, de…
Coarse-to-Fine Grounded Memory for LLM Agent Planning
Wei Yang, Jinwei Xiao, Hongming Zhang +3
Recent advancements in Large Language Models (LLMs) have driven growing interest in LLM-based agents for complex planning tasks. To avoid costly agent training, many studies adopte…
Self-Guided Function Calling in Large Language Models via Stepwise Experience Recall
Sijia Cui, Aiyao He, Shuai Xu +5
Function calling enables large language models (LLMs) to interact with external systems by leveraging tools and APIs. When faced with multi-step tool usage, LLMs still struggle wit…