12 papers
Slides2MindMap: Reconstructing Cognitively Efficient Knowledge Hierarchies from Lecture Slides
Yuzhi Wang, Rongjun Ye, Shengyuan Chen +5
Generating mind maps from lecture slides can help learners efficiently assimilate fragmented knowledge, promising substantial benefits for intelligent education. However, dedicated…
Zero-Mem: Zero-Token Memory Operations for LLM Agents
Yilin Xiao, Zhehan Zhu, Yujing Zhang +8
LLM agents need memory to act consistently over long interactions, yet many systems use additional LLM calls to operate that memory. Generating intermediate records and mediating t…
When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation
Zhishang Xiang, Chuanjie Wu, Qinggang Zhang +4
Graph retrieval-augmented generation (GraphRAG) has emerged as a powerful paradigm for enhancing large language models (LLMs) with external knowledge. It leverages graphs to model…
Graph-based Agent Memory: Taxonomy, Techniques, and Applications
Chang Yang, Chuang Zhou, Yilin Xiao +15
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…
Use Graph When It Needs: Efficiently and Adaptively Integrating Retrieval-Augmented Generation with Graphs
Su Dong, Qinggang Zhang, Yilin Xiao +3
Large language models (LLMs) often struggle with knowledge-intensive tasks due to hallucinations and outdated parametric knowledge. While Retrieval-Augmented Generation (RAG) addre…
LAG: Logic-Augmented Generation from a Cartesian Perspective
Yilin Xiao, Chuang Zhou, Yujing Zhang +5
Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet exhibit critical limitations in knowledge-intensive tasks, often generating…