2025Q3 Reports: SIGSUMM
SIGSUMM
SIGSUMM is the Association for Computational Linguistics special interest group for summarization. Founded in 2023, SIGSUMM is one of ACL’s SIGs. Its primary mission since its inception has been to organize a series of workshops, including NEWSUMM (New Frontiers in Summarization Workshops). SIGSUMM is generally focused on corpus-based, statistical or deep learning methods in automatic text summarization, and encourages initiatives in support of this broader mission from its members.
Membership
SIGSUMM has a total of over 110 members from various backgrounds, including students, academics, and professionals in the fields of Computational Linguistics, Summarization, Machine Learning, and Artificial Intelligence. Membership has grown steadily since its founding, reflecting the expanding interest in summarization research in the era of large language models and multimodal systems.
Officers
The officers of SIGSUMM include:
- Yue Dong, Assistant Professor at University of California, Riverside, Liaison Representative
- Wen Xiao, Researcher at Microsoft Azure Cognitive Service
- Yumo Xu, Scientist at AWS AI Labs Seattle
- Lu Wang, Associate Professor at the University of Michigan
- Fei Liu, Associate Professor at Emory University
- Jackie Chit Kit Cheung, Associate Professor at McGill University
- Giuseppe Carenini, Professor at the University of British Columbia
- Mirella Lapata, Professor at the University of Edinburgh
- Ido Dagan, Professor at Bar-Ilan University
Elections
The next SIGSUMM officer election will be held in December 2025. Nominations and details will be circulated via the mailing list and the SIGSUMM website.
Activities
SIGSUMM organizes the NEWSUMM Workshops, including the 5th NewSumm workshop that will take place at EMNLP 2025. The workshop continues to expand its scope to address:
- Grounded and retrieval-augmented summarization
- Multi-modal summarization and auditing using MLLMs
- Hallucination detection and factuality evaluation
- Query-focused and task-adaptive summarization
- Efficient summarization for edge and mobile applications
External Links
Official Website SIGSUMM Website
Mailing List SIGSUMM Mailing List