Papers by Zhiyun Lu

2 papers
A Large Scale Speech Sentiment Corpus (2020.lrec-1)

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Challenge: Existing corpus for sentiment analysis uses text inputs, but voice inputs are becoming more important as smart assistants and mobile voice control become more prevalent.
Approach: They propose to extend the Switchboard-1 Telephone Speech Corpus by adding sentiment labels from 3 different human annotators for every transcript segment.
Outcome: The proposed corpus contains 49500 labeled speech segments covering 140 hours of audio.
Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation (2024.acl-long)

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Challenge: Existing methods to evaluate preference data without human annotations are difficult . et al., 2022b) is effective for aligning large language models with human expectations .
Approach: They propose a method to evaluate the response preference using output probabilities under contrastive prompts.
Outcome: The proposed method could surpass the RLHF method without human-annotated preference data.

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