===Call for Main Conference Papers===
EMNLP 2024 invites the submission of long and short papers featuring substantial, original, and unpublished research on empirical methods for Natural Language Processing. EMNLP 2024 has a goal of a diverse technical program -- in addition to traditional research results, papers may contribute negative findings, survey an area, announce the creation of a new resource, argue a position, report novel linguistic insights derived using existing computational techniques, and reproduce, or fail to reproduce, previous results.
As in recent years, some of the presentations at the conference will be of papers accepted by the Transactions of the ACL (TACL) and the Computational Linguistics (CL) journals.
EMNLP 2024 will be held in the Hyatt Regency Miami in Miami, Florida (USA).
===Paper Submission Information===
EMNLP will accept submissions through ARR only. Papers may be submitted to the ARR 2024 June cycle (link to be provided later).
Papers that have received reviews and a meta-review from ARR (whether from the ARR 2024 June cycle or an earlier ARR cycle) may be committed to EMNLP (link to be provided later).
For detailed submission information, please refer to our webpage: https://2024.emnlp.org
===Important Dates===
ARR submission deadline: June 15, 2024
Commitment deadline for EMNLP 2024: August 20, 2024
Notification of acceptance (long and short papers): September 20, 2024
Camber-ready papers due (long and short): October 3, 2024
Main Conference: November 12-14, 2024
Workshop and Tutorials: November 15-16, 2024
Note: All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”).
Following the ACL and ARR policies, there is no anonymity period requirement.
===Submission Topics===
EMNLP 2024 aims to have a broad technical program. Relevant topics for the conference include, but are not limited to, the following areas:
- Computational Social Science and Cultural Analytics
- Dialogue and Interactive Systems
- Discourse and Pragmatics
- Low-resource Methods for NLP
- Ethics, Bias, and Fairness
- Generation
- Information Extraction
- Information Retrieval and Text Mining
- Interpretability and Analysis of Models for NLP
- Linguistic theories, Cognitive Modeling and Psycholinguistics
- Machine Learning for NLP
- Machine Translation
- Multilinguality and Language Diversity
- Multimodality and Language Grounding to Vision, Robotics and Beyond
- Phonology, Morphology and Word Segmentation
- Question Answering
- Resources and Evaluation
- Semantics: Lexical, Sentence-level Semantics, Textual Inference and Other areas
- Sentiment Analysis, Stylistic Analysis, and Argument Mining
- Speech processing and spoken language understanding
- Summarization
- Syntax: Tagging, Chunking and Parsing
- NLP Applications
- Special Theme: Efficiency in Model Training and Inference: Addressing Data Requirements and Model Size
===EMNLP 2024 Theme Track: Efficiency in Model Algorithms, Training, and Inference===
This track provides a platform for researchers to explore key aspects of making model algorithms, training, and inference more efficient, e.g., quantization, data requirements, and model size. We welcome submissions that propose innovative approaches, methodologies, and techniques to streamline the training and inference process for language models while optimizing resource utilization and reducing model size. Authors are encouraged to explore various ways to enhance efficiency, including parameter-efficient tuning and methods for learning with less data and smaller model sizes, ultimately leading to more scalable, practical, and resource-efficient NLP systems.
Visit https://2024.emnlp.org for more
For questions related to paper submission, and the review process in general, email: editors [at] aclrollingreview.org
For all other questions email: emnlp2024-programchairs [at] googlegroups.com