Papers by Pichao Wang

2 papers
CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation (2025.findings-acl)

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Challenge: Large language models (LLMs) have shown great potential in natural language processing tasks, but their application to machine translation remains challenging due to pretraining on predominantly English-centric datasets.
Approach: They propose a method that combines reward scores with model confidence to improve model selection for fine-tuning.
Outcome: The proposed method outperforms existing methods in translation accuracy and data efficiency.
Do Audio LLMs Really LISTEN, or Just Transcribe? Measuring Lexical vs. Acoustic Emotion Cues Reliance (2026.eacl-long)

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Challenge: LISTEN is a controlled benchmark to disentangle lexical reliance from acoustic sensitivity in emotion understanding.
Approach: They propose a benchmark to disentangle lexical reliance from acoustic sensitivity in emotion understanding.
Outcome: LISTEN shows that current LALMs largely "transcribe" rather than "listen" authors note that models underutilize acoustic cues while relying on lexical semantics .

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