Empirical Methods in Natural Language Processing (EMNLP) 2025
Apple is presenting new work at the annual Empirical Methods in Natural Language Processing (EMNLP) conference, which takes place in person from November 4 – 9, in Suzhou, China. EMNLP focuses on research surrounding the science and technology of spoken language processing.
Below is the schedule of Apple-sponsored workshops and events at EMNLP 2025.
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Schedule
Stop by the Apple booth in the Suzhou International Expo Center during exhibition hours. All times listed in CST (Suzhou local time):
- Wednesday, November 5: 09:00 – 18:00
- Thursday, November 6: 09:00 – 18:00
- Friday, November 7: 09:00 – 16:00
Schedule
Wednesday, November 5
- DEMO
- MLX
- 09:00 – 18:00, Apple Booth
- We demonstrate large model inference and training on device using MLX. MLX is a flexible array framework that is optimized for Apple silicon and brought to you by Apple machine learning research. It enables training and inference of arbitrarily complex models on Apple silicon powered devices with great brevity and flexibility.
- PRESENTATION, POSTER
- Evaluating Evaluation Metrics — The Mirage of Hallucination Detection
- 13:00 – 14:00, Findings 1, Hall C3
- Atharva Kulkarni (USC), Yuan Zhang, Joel Ruben Antony Moniz (DoorDash), Hugh Ge, Andy Tseng, Dhivya Piraviperumal, Swabha Swayamdipta (USC), Hong Yu
Thursday, November 6
- DEMO
- MLX
- 9:00 – 18:00, Apple Booth
- We demonstrate large model inference and training on device using MLX. MLX is a flexible array framework that is optimized for Apple silicon and brought to you by Apple machine learning research. It enables training and inference of arbitrarily complex models on Apple silicon powered devices with great brevity and flexibility.
Friday, November 7
- WORKSHOP
- PolyNorm: Few-Shot LLM-Based Text Normalization for Text-to-Speech
- 08:00 – 09:00, Gather Session 4 (Virtual)
- Michel Wong, Haotian He, Ali Alshehri, Sophia Kao
Saturday, November 8
Accepted Papers
AuthorsEileen Pan†, Anna Seo Gyeong Choi†, Maartje ter Hoeve, Skyler Seto, Allison Koenecke†‡
Assessing the Role of Data Quality in Training Bilingual Language Models
Skyler Seto, Maartje ter Hoeve, Maureen de Seyssel, David Grangier
AuthorsNivedha Sivakumar*, Natalie Mackraz*, Samira Khorshidi, Krishna Patel†, Barry-John Theobald, Luca Zappella, Nicholas Apostoloff
AuthorsXinze Wang, Chen Chen, Yinfei Yang, Hong-You Chen, Bowen Zhang, Aditya Pal, Xiangxin Zhu, Xianzhi Du
AuthorsMaureen de Seyssel*, Jie Chi*, Skyler Seto, Maartje ter Hoeve, Masha Fedzechkina, Natalie Schluter
AuthorsAtharva Kulkarni†*, Yuan Zhang, Joel Ruben Antony Moniz*, Xiou Ge, Bo-Hsiang Tseng, Dhivya Piraviperumal, Swabha Swayamdipta†, Hong Yu
AuthorsBrihi Joshi**†, Xiang Ren†, Swabha Swayamdipta†, Rik Koncel-Kedziorski, Tim Paek
AuthorsYajie Li†, Albert Galimov†, Mitra Datta Ganapaneni†, Pujitha Thejaswi†, De Meng, Priyanshu Kumar, Saloni Potdar
AuthorsCongzheng Song, Xinyu Tang
PolyNorm: Few-Shot LLM-Based Text Normalization for Text-to-Speech
Michel Wong, Haotian He, Ali Alshehri, Sophia Kao
AuthorsRik Koncel-Kedziorski, Brihi Joshi†, Tim Paek
AuthorsNikhil Bhendawade, Irina Belousova, Qichen Fu, Henry Mason, Mohammad Rastegari, Mahyar Najibi
AuthorsMatthias Sperber, Maureen de Seyssel, Jiajun Bao, Matthias Paulik
Acknowledgements
Saloni Potdar is an Industry Track Chair for EMNLP 2025.
Qingqing Cao and Natalie Schluter are Senior Area Chairs.
Richard Bai, Maartje ter Hoeve, Chao Jiang, Rik Koncel-Kedziorski, and Yizhe Zhang are Area Chairs.
Jason Dong, Lu Ren and Shu W. are Session Chairs.
Richard Bai is a Workshop Co-Organizer for Widening Natural Language Processing (WiNLP).
Maartje ter Hoeve, Katherine Metcalf, and Andrew Silva are Workshop Co-Organizers for Tailoring AI: Exploring Active and Passive LLM Personalization (PALS).
Natalie Schluter and Barry-John Theobald serve on the Workshop Advisory Board for Tailoring AI: Exploring Active and Passive LLM Personalization (PALS).
Maureen de Seyssel is a Workshop Reviewer for Tailoring AI: Exploring Active and Passive LLM Personalization (PALS).
Aswarth Abhilash Dara, Mozhdeh Gheini, and Stephan Peitz are Reviewers for the EMNLP 2025 Industry Track.
Arnav Arora, Jie Chi, Jason Dong, Qin Gao, Xintong Li, De Meng, Alex Papangelis, Shuwen Qiu, Robin Schmidt, Dayu Wang, and Hong Yu are Reviewers for EMNLP 2025.
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