Papers by Gary Ushaw

2 papers
MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperation (2026.acl-long)

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Challenge: Embodied AI systems are open, where agents may leave or enter mid-task due to hardware failures or task-related errors.
Approach: They propose a framework that reformulates credit assignment as a rank aggregation problem using contribution-based pairwise comparisons among agents generated by large multimodal models.
Outcome: The proposed framework can guide agents toward effective cooperation in complex tasks of different types.
Tracing the Light of Thought: A Probabilistic Self- and Cross-Consistency Verification Mechanism Improving Mathematical Reasoning in LLMs (2026.findings-acl)

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Challenge: Existing methods for evaluating reasoning paths are not efficient, but they are prone to errors.
Approach: They propose a probabilistic self- and cross-consistency framework for mathematical reasoning that employs an accept-reject mechanism to encourage high-quality reasoning paths.
Outcome: The proposed framework improves on 9 LLMs across 4 challenging benchmarks.

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