Papers by Zehao Jin

2 papers
OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agents (2026.acl-long)

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Challenge: Vision-Language Models (VLMs) lack visual-aware tutorial retrieval and historical visual context curation and pruning.
Approach: They propose a framework that integrates an orchestrator and a Reflection-Memory Agent for robust automation.
Outcome: Experimental results show that OS-Symphony delivers substantial performance gains across model scales.
SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures (2026.findings-acl)

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Challenge: Large language models (LLMs) are widely deployed as domain-specific agents, but evaluation of their capabilities in such contexts has not been fully explored.
Approach: They propose a benchmark to evaluate LLMs' ability to follow instructions and make decisions in real-world scenarios.
Outcome: The proposed benchmark is constructed from real-world business data and adapted into 23 complex SOP scenarios.

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