6 papers
MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research
Dingbang Wu, Rui Hao, Haiyang Wang +8
We present MobileGym, a browser-hosted, lightweight, fully controllable environment for everyday mobile use, targeting interaction fidelity without replicating proprietary backends…
On the Hidden Costs of Counterfactual Knowledge Training in LLM Unlearning
Xiaotian Ye, Xiaohan Wang, Mengqi Zhang +1
Counterfactual tuning (CFT) has emerged as a promising paradigm for Large Language Model (LLM) unlearning by training models to generate alternative fictitious knowledge in place o…
Claw-Anything: Benchmarking Always-On Personal Assistants with Broader Access to User's Digital World
Yusong Lin, Xinyuan Liang, Haiyang Wang +8
Large language model agents are increasingly envisioned as always-on personal assistants with access to anything relevant in the user's digital world. Yet current systems operate o…
Visual-Advantage On-Policy Distillation for Vision-Language Models
Ruiqi Liu, Xiaolei Lv, Gengsheng Li +8
On-policy knowledge distillation has proven effective for language models, yet its application to vision-language models (VLMs) remains underexplored. We observe that standard on-p…
CLI-Gym: Scalable CLI Task Generation via Agentic Environment Inversion
Yusong Lin, Haiyang Wang, Shuzhe Wu +4
Agentic coding requires agents to effectively interact with runtime environments, e.g., command line interfaces (CLI), so as to complete tasks like resolving dependency issues, fix…
FeatureBench: Benchmarking Agentic Coding for Complex Feature Development
Qixing Zhou, Jiacheng Zhang, Haiyang Wang +9
Agents powered by large language models (LLMs) are increasingly adopted in the software industry, contributing code as collaborators or even autonomous developers. As their presenc…