75 citations · 111 across the 10 of their papers we have counts for
6 papers · 1 filter
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Weijian Qi +2
Our ability to continuously acquire, organize, and leverage knowledge is a key feature of human intelligence that AI systems must approximate to unlock their full potential. Given…
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu +2
In order to thrive in hostile and ever-changing natural environments, mammalian brains evolved to store large amounts of knowledge about the world and continually integrate new inf…
Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments
Yu Gu, Yiheng Shu, Hao Yu +6
The applications of large language models (LLMs) have expanded well beyond the confines of text processing, signaling a new era where LLMs are envisioned as generalist agents capab…
Data Distribution Bottlenecks in Grounding Language Models to Knowledge Bases
Yiheng Shu, Zhiwei Yu
Language models (LMs) have already demonstrated remarkable abilities in understanding and generating both natural and formal language. Despite these advances, their integration wit…
Question Decomposition Tree for Answering Complex Questions over Knowledge Bases
Xiang Huang, Sitao Cheng, Yiheng Shu +2
Knowledge base question answering (KBQA) has attracted a lot of interest in recent years, especially for complex questions which require multiple facts to answer. Question decompos…
TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge Bases
Yiheng Shu, Zhiwei Yu, Yuhan Li +4
Pre-trained language models (PLMs) have shown their effectiveness in multiple scenarios. However, KBQA remains challenging, especially regarding coverage and generalization setting…