collaborators

9 papers

cs.CL2026

MExam: Benchmarking Multimodal Memory for Realistic User-Agent Interactions

Zhengjun Huang, Wenxuan Liu, Zhoujin Tian +6

Language agents are increasingly deployed over accumulating multimodal information, yet existing benchmarks assume a human-human form with sparse visuals and straightforward conten…

cs.CL2026

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…

cs.DB2026

Cardinality Estimation for High Dimensional Similarity Queries with Adaptive Bucket Probing

Zhonghan Chen, Qintian Guo, Ruiyuan Zhang +1

In this work, we address the problem of cardinality estimation for similarity search in high-dimensional spaces. Our goal is to design a framework that is lightweight, easy to cons…

cs.CL2026

Breaking the Static Graph: Context-Aware Traversal for Robust Retrieval-Augmented Generation

Kwun Hang Lau, Fangyuan Zhang, Boyu Ruan +4

Recent advances in Retrieval-Augmented Generation (RAG) have shifted from simple vector similarity to structure-aware approaches like HippoRAG, which leverage Knowledge Graphs (KGs…

cs.IR2026

LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning

Zhengjun Huang, Zhoujin Tian, Qintian Guo +5

Large Language Model (LLM) agents exhibit remarkable conversational and reasoning capabilities but remain constrained by limited context windows and the lack of persistent memory.…

cs.DB2025

ACGraph: An Efficient Asynchronous Out-of-Core Graph Processing Framework

Dechuang Chen, Sibo Wang, Qintian Guo

Graphs are a ubiquitous data structure in diverse domains such as machine learning, social networks, and data mining. As real-world graphs continue to grow beyond the memory capaci…