Papers by Yi Shan

3 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.
Read Anywhere Pointed: Layout-aware GUI Screen Reading with Tree-of-Lens Grounding (2024.emnlp-main)

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Challenge: Existing models for GUI understanding ignore a key GUI-referring task: screen reading based on user-indicated points.
Approach: They propose a Tree-of-Lens agent that constructs a Hierarchical Layout Tree based on user input points and a GUI screenshot.
Outcome: The proposed agent can interpret the Screen Point-and-Read task on mobile, web, and operating systems.
GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning (2026.findings-acl)

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Challenge: Recent reinforcement learning approaches have advanced reasoning in Large Language Models (LLMs), yet their adaptation to multimodal LLMs remains underexplored.
Approach: They propose a reinforcement learning framework that eliminates KL penalties and rewards consistency . they propose GRPO-CARE, which outperforms standard GR PO, with a base reward for accuracy and an adaptive bonus for consistency.
Outcome: The proposed framework outperforms standard GRPO on the most difficult evaluation level and reasoning consistency test benchmarks.

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