Papers by Tingyu Cao

2 papers
Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration (2025.acl-long)

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Challenge: Large language models (LLMs) excel in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction.
Approach: They propose a language agent framework that integrates *System 1* and *System 2* for efficient real-time simultaneous human-AI collaboration.
Outcome: The proposed framework improves on existing LLM-based agents and human collaborators by integrating Theory of Mind and asynchronous reflection to infer human intentions and perform reasoning-based autonomous decisions.
Specialization through Collaboration: Understanding Expert Interaction in Mixture-of-Expert Large Language Models (2026.eacl-long)

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Challenge: Mixture-of-Experts (MoE) based large language models are popular for multitasking . however, whether each expert can specialize to a task remains unclear .
Approach: They propose to use a dictionary learning approach to analyze expert collaboration mechanisms in MoE LLMs.
Outcome: The proposed model outperforms existing methods by 2.5% while enabling 50% expert reduction.

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