7 citations · 7 across the 13 of their papers we have counts for
4 papers · 1 filter
H-Mem: A Novel Memory Mechanism for Evolving and Retrieving Agent Memory via a Hybrid Structure
Jiawei Yu, Yixiang Fang, Xilin Liu +1
Memory data are ubiquitous in Large Language Model (LLM)-based agents (e.g., OpenClaw and Manus). A few recent works have attempted to exploit agents'memory for improving their per…
ASTRA-QA: A Benchmark for Abstract Question Answering over Documents
Shu Wang, Shansong Zhou, Xinyang Wang +3
Document-based question answering (QA) increasingly includes abstract questions that require synthesizing scattered information from long documents or across multiple documents int…
SkillRAE: Agent Skill-Based Context Compilation for Retrieval-Augmented Execution
Xiangcheng Meng, Shu Wang, Yixiang Fang
Large Language Model (LLM)-based agents (e.g., OpenClaw) increasingly rely on reusable skill libraries to solve artifact-rich tasks such as document-centric workflows and data-inte…
Memory in the LLM Era: Modular Architectures and Strategies in a Unified Framework
Yanchen Wu, Tenghui Lin, Yingli Zhou +7
Memory emerges as the core module in the large language model (LLM)-based agents for long-horizon complex tasks (e.g., multi-turn dialogue, game playing, scientific discovery), whe…