Zhaoxuan Jin — accepted AI-conference papers

2025

CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents

Tianqi Xu, Linyao Chen, Dai-Jie Wu, Yanjun Chen, Zecheng Zhang, Xiang Yao +10

ACL 2025finding

The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites, desktop computers, or mobile phones. Existing benchmarks for MLM agents in interactive environments are limited by the…

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2025

OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Mengkang Hu, Yuhang Zhou, Wendong Fan, Yuzhou Nie, Ziyu Ye, Bowei Xia +9

NeurIPS 2025poster

Large Language Model (LLM)-based multi-agent systems show promise for automating real-world tasks but struggle to transfer across domains due to their domain-specific nature. Current approaches face two critical shortcomings: they require complete architectural redesign and full retraining of all co…

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