NeKo: Cross-Modality Post-Recognition Error Correction with Tasks-Guided Mixture-of-Experts Language Model
Yen-Ting Lin, Zhehuai Chen, Piotr Zelasko, Zhen Wan, Xuesong Yang, Zih-Ching Chen, Krishna C Puvvada, Ke Hu, Szu-Wei Fu, Jun Wei Chiu, Jagadeesh Balam, Boris Ginsburg, Yu-Chiang Frank Wang, Chao-Han Huck Yang. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track). 2025.
Authors
- Zhehuai Chen (ORCID: https://orcid.org/0000-0003-4400-5340)
- Zih-Ching Chen
- Yen‐Ting Lin (ORCID: https://orcid.org/0000-0001-7146-4687)
- Chao-Han Huck Yang (ORCID: https://orcid.org/0000-0003-2879-8811)
- Piotr Żelasko (ORCID: https://orcid.org/0000-0002-8245-0413)
- Ke Hu (ORCID: https://orcid.org/0000-0002-1599-1519)
- Boris Ginsburg
- Jennifer L. Chiu (ORCID: https://orcid.org/0000-0001-7663-5748)
- Jagadeesh Balam
- Xuesong Yang (ORCID: https://orcid.org/0000-0001-8625-5044)
- Krishna C. Puvvada
- Szu‐Wei Fu (ORCID: https://orcid.org/0000-0002-3487-8212)
- Yu-Chiang Frank Wang (ORCID: https://orcid.org/0000-0002-2333-157X)
- Zhen Wan
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.acl-industry.17
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Nvidia