Publications

My research publications with papers, code, and datasets.

Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
Potsawee Manakul, Woody Haosheng Gan, Martijn Bartelds, Guangzhi Sun, William Held, Diyi Yang
arXiv preprint
2026
Paper Code Models Website
Putting HUMANS first: Efficient LAM Evaluation with Human Preference Alignment
Putting HUMANS first: Efficient LAM Evaluation with Human Preference Alignment
Woody Haosheng Gan, William Held, Diyi Yang
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026 Main)
2026
Paper Code Dataset
AudioJudge: Understanding what works in large audio model based speech evaluation
AudioJudge: Understanding what works in large audio model based speech evaluation
Potsawee Manakul*, Woody Haosheng Gan*, Michael J. Ryan, Ali Sartaz Khan, Warit Sirichotedumrong, Kunat Pipatanakul, William Held, Diyi Yang
* Equal contribution
Proceedings of the 21st Conference of the European Chapter of the Association for Computational Linguistics (EACL 2026 Main)
2025
Paper Code
Textual steering vectors can improve visual understanding in multimodal large language models
Textual steering vectors can improve visual understanding in multimodal large language models
Woody Haosheng Gan*, Deqing Fu*, Julian Asilis*, Ollie Liu*, Dani Yogatama, Vatsal Sharan, Robin Jia, Willie Neiswanger
* Equal contribution
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026 Main)
2025
Paper Code Blog
ConceptMix++: Leveling the playing field in text-to-image benchmarking via iterative prompt optimization
ConceptMix++: Leveling the playing field in text-to-image benchmarking via iterative prompt optimization
Haosheng Gan, Berk Tinaz, Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi
3rd Workshop on Generative Models for Computer Vision (GMCV), CVPR 2025
2025
Paper
Differentially private in-context learning via sampling few-shot mixed with zero-shot outputs
Differentially private in-context learning via sampling few-shot mixed with zero-shot outputs
James Flemings, Haosheng Gan, Hongyi Li, Meisam Razaviyayn, Murali Annavaram
arXiv preprint
2025
Paper Code