EMNLP

The 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP) is a premier academic conference focused on empirical methods in natural language processing research. The conference brings together researchers, practitioners, and industry professionals to share cutting-edge advances in computational linguistics and machine learning applications to language understanding.

The conference is organized by ACL’s SIGDAT (Special Interest Group on Linguistic Data and Corpus-Based Approaches to NLP). EMNLP has established itself as one of the most important venues for publishing high-quality research in natural language processing, covering topics from neural machine translation to sentiment analysis.

Attendees can expect presentations of peer-reviewed research papers, workshops, tutorials, and poster sessions. The conference provides opportunities for networking with leading researchers and discovering the latest developments in areas like large language models, multilingual NLP, and computational semantics.

The event follows a rigorous review process through the ACL Rolling Review system, ensuring only the highest quality research is presented. Authors submit their work through ARR (ACL Rolling Review) before committing their papers to the EMNLP venue.

Budapest provides an inspiring backdrop for this gathering of the NLP community. The city’s rich academic tradition and cultural heritage create an ideal environment for scholarly exchange and collaboration among international researchers working on language technologies.