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20242026
most citedAdvances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

16 citations · 35 across the 10 of their papers we have counts for

collaborators

12 papers

cs.AI2026

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…

cs.CL2026

SkillHarm: Lifecycle-Aware Skill-Based Attacks via Automated Construction

Yuting Ning, Zhehao Zhang, Yash Kumar Lal +8

Agent skills occupy a privileged position in the agent workflow, as agents are expected to implicitly follow and execute them, rendering third-party skills a vulnerable attack surf…

cs.AI2026

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…

cs.AI2025

WebGuard: Building a Generalizable Guardrail for Web Agents

Boyuan Zheng, Zeyi Liao, Scott Salisbury +8

The rapid development of autonomous web agents powered by Large Language Models (LLMs), while greatly elevating efficiency, exposes the frontier risk of taking unintended or harmfu…

cs.AI2025

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…

cs.AI2025★ 16 cited

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Bang Liu, Xinfeng Li, Jiayi Zhang +45

The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…

cs.AI2025

An Illusion of Progress? Assessing the Current State of Web Agents

Tianci Xue, Weijian Qi, Tianneng Shi +5

As digitalization and cloud technologies evolve, the web is becoming increasingly important in the modern society. Autonomous web agents based on large language models (LLMs) hold…

cs.AI2024

Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents

Yu Gu, Kai Zhang, Yuting Ning +9

Language agents based on large language models (LLMs) have demonstrated great promise in automating web-based tasks. Recent work has shown that incorporating advanced planning algo…

cs.AI2024★ 3 cited

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…

cs.CL2024★ 6 cited

ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

Ziru Chen, Shijie Chen, Yuting Ning +17

The advancements of large language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked…

cs.CL2024

A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents

Lingbo Mo, Zeyi Liao, Boyuan Zheng +3

Language agents powered by large language models (LLMs) have seen exploding development. Their capability of using language as a vehicle for thought and communication lends an incr…

cs.IR2024★ 10 cited

GPT-4V(ision) is a Generalist Web Agent, if Grounded

Boyuan Zheng, Boyu Gou, Jihyung Kil +2

The recent development on large multimodal models (LMMs), especially GPT-4V(ision) and Gemini, has been quickly expanding the capability boundaries of multimodal models beyond trad…