Papers by Feiran Liu

2 papers
SILO-BENCH: A Scalable Environment for Evaluating Distributed Coordination in Multi-Agent LLM Systems (2026.acl-long)

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Challenge: Existing benchmarks conflate coordination ability with role-based priors.
Approach: They propose a role-free benchmark for evaluating free-form collaboration under information silos.
Outcome: The proposed benchmark systematically probes coordination capabilities under information silos using 54 configurations and 3 frontier LLMs.
Don’t Act Blindly: Robust GUI Automation via Action-Effect Verification and Self-Correction (2026.acl-long)

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Challenge: Existing GUI agents assume deterministic environment responses, generating actions without verifying whether previous operations succeeded.
Approach: They propose a GUI agent that explicitly models action outcomes and recovery under noisy environments.
Outcome: The proposed agent reduces failure loops and improves recovery success in noisy environments while maintaining competitive standard task performance.

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