1 citations · 1 across the 5 of their papers we have counts for
6 papers
OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software
Dingyuan Dai, Heli Qi, Lei Liu +28
Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires interpreting specialized int…
Qwen-CUA: Native Computer Use for (almost) Everything
Dunjie Lu, Shuai Bai, Tianyi Bai +42
Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking, large-scale interactive expe…
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…
SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents via Distilled Structured Reasoning
Kaiwen Zhou, Ahmed Elgohary, A S M Iftekhar +1
The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring…
AdvAgent: Controllable Blackbox Red-teaming on Web Agents
Chejian Xu, Mintong Kang, Jiawei Zhang +5
Foundation model-based agents are increasingly used to automate complex tasks, enhancing efficiency and productivity. However, their access to sensitive resources and autonomous de…
Direct Multi-Turn Preference Optimization for Language Agents
Wentao Shi, Mengqi Yuan, Junkang Wu +2
Adapting Large Language Models (LLMs) for agent tasks is critical in developing language agents. Direct Preference Optimization (DPO) is a promising technique for this adaptation w…