Papers by Yu-An Su

2 papers
Compete to Complete: Co-opetition Adversarial Learning for Retrieval-Augmented Generation (2026.acl-long)

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Challenge: Existing approaches to reduce hallucination in large language models lack a robust mechanism for generating a generative model.
Approach: They propose a framework that formulates retriever–generator training in RAG as a minimax game.
Outcome: The proposed framework improves retrieval-augmented generation performance on seven benchmark datasets.
CoachMe: Decoding Sport Elements with a Reference-Based Coaching Instruction Generation Model (2025.acl-long)

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Challenge: Existing multimodal models for motion related tasks have shown significant progress.
Approach: They propose a reference-based model that analyzes the differences between a learner’s motion and a physical reference under temporal and physical aspects.
Outcome: The proposed model outperforms GPT-4o on figure skating and boxing by 31.6% and 58.3% respectively.

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