30 citations · 78 across the 17 of their papers we have counts for
7 papers · 1 filter
OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
Mengqi Yuan, Zilong Zhou, Xinzhuang Xiong +33
Existing computer-use benchmarks fail to capture the realism, complexity, and long-horizon demands of real-world computer use, limiting their ability to reveal the limitations of f…
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…
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…
SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills
Boyuan Zheng, Michael Y. Fatemi, Xiaolong Jin +8
To survive and thrive in complex environments, humans have evolved sophisticated self-improvement mechanisms through environment exploration, hierarchical abstraction of experience…
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…
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…
Learn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation
Yukun Feng, Feng Li, Ziang Song +2
The Transformer architecture has led to significant gains in machine translation. However, most studies focus on only sentence-level translation without considering the context dep…