75 citations · 111 across the 10 of their papers we have counts for
11 papers
AgentCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
Yiheng Shu, Bernal Jiménez Gutiérrez, Saisri Padmaja Jonnalagedda +3
Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future episodes. Continual learning…
REMem: Reasoning with Episodic Memory in Language Agent
Yiheng Shu, Saisri Padmaja Jonnalagedda, Xiang Gao +5
Humans excel at remembering concrete experiences along spatiotemporal contexts and performing reasoning across those events, i.e., the capacity for episodic memory. In contrast, me…
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Boyu Gou, Zanming Huang, Yuting Ning +23
Agentic search such as Deep Research systems-where agents autonomously browse the web, synthesize information, and return comprehensive citation-backed answers-represents a major s…
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…
Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
Boyu Gou, Ruohan Wang, Boyuan Zheng +5
Multimodal large language models (MLLMs) are transforming the capabilities of graphical user interface (GUI) agents, facilitating their transition from controlled simulations to co…
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…
Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
Hui Fang, Danning Zhang, Yiheng Shu +1
In the field of sequential recommendation, deep learning (DL)-based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov c…