most citedFrom Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Query-Centric Graph Retrieval Augmented Generation

Yaxiong Wu, Jianyuan Bo, Yongyue Zhang +2

Graph-based retrieval-augmented generation (RAG) enriches large language models (LLMs) with external knowledge for long-context understanding and multi-hop reasoning, but existing…

cs.CL2025

Schema as Parameterized Tools for Universal Information Extraction

Sheng Liang, Yongyue Zhang, Yaxiong Wu +2

Universal information extraction (UIE) primarily employs an extractive generation approach with large language models (LLMs), typically outputting structured information based on p…

cs.CL2025

Effective and Efficient Schema-aware Information Extraction Using On-Device Large Language Models

Zhihao Wen, Sheng Liang, Yaxiong Wu +2

Information extraction (IE) plays a crucial role in natural language processing (NLP) by converting unstructured text into structured knowledge. Deploying computationally intensive…

cs.IR20252 cited

From Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs

Yaxiong Wu, Sheng Liang, Chen Zhang +5

Memory is the process of encoding, storing, and retrieving information, allowing humans to retain experiences, knowledge, skills, and facts over time, and serving as the foundation…

cs.IR2024

All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era

Bo Chen, Xinyi Dai, Huifeng Guo +9

Recommender systems (RS) are vital for managing information overload and delivering personalized content, responding to users' diverse information needs. The emergence of large lan…