EACL 2027 (Conference of the European Chapter of the Association for Computational Linguistics) is a ICORE A conference held in Athens, Greece on 2027-03-09. The paper submission deadline is 2026-08-03. Acceptance notifications are sent on 2026-11-12.
EACL 2027 aims to have a broad technical program. Relevant topics for the conference include, but are not limited to, the following areas:
Clinical and Biomedical Applications
Computational Social Science and Cultural Analytics
Dialogue and Interactive Systems
Discourse and Pragmatics
Efficient Methods for NLP
Ethics, Bias, and Fairness
Generation
Human-Centered NLP and Human-AI Interaction
Information Extraction
Information Retrieval and Text Mining
Interpretability and Analysis of Models for NLP
Language Modeling
LLM Agents
Linguistic Theories, Cognitive Modeling, and Psycholinguistics
Machine Learning for NLP
Machine Translation
Multilingualism and Cross-Lingual NLP
Multimodality and Language Grounding to Vision, Robotics and Beyond
NLP Applications
NLP and Code Models
NLP and Symbolic Reasoning
Phonology, Morphology, and Word Segmentation
Question Answering
Resources and Evaluation
Semantics: Lexical and Sentence-Level
Sentiment Analysis, Stylistic Analysis, and Argument Mining
Speech Recognition, Text-to-Speech and Spoken Language Understanding
Summarization
Syntax: Tagging, Chunking and Parsing
EACL 2027 Special Theme: The Human in Language
Natural language processing has historically been grounded in the scientific study of human language. Linguistics, psycholinguistics, cognitive science, sociolinguistics, and related disciplines have shaped many of the core concepts underlying NLP, including syntax, semantics, discourse, pragmatics, language acquisition, and communication. Yet, as modern NLP increasingly shifts toward large-scale end-to-end learning and benchmark-driven evaluation, the connection between language technologies and the broader scientific understanding of human language is often becoming less explicit.
The EACL 2027 special theme, The Human in Language, invites papers that explore how the human sciences of language can inform and shape NLP research across the full research cycle: model development, representation learning, data collection and annotation, evaluation, interpretability, interaction, and deployment. We particularly encourage work that brings linguistic and cognitive insights into the design and analysis of NLP systems, develops evaluation methodologies grounded in human language behavior and communication, and revisits foundational questions about what language technologies should model and optimize for.
At the same time, we also welcome work that uses NLP methods and contemporary language models to advance the scientific study of language, cognition, communication, and the brain. However, the central focus of the track is on strengthening the role of language sciences as a source of scientific grounding, methodological guidance, and conceptual insight for NLP itself.
Relevant topics include, but are not limited to:
Linguistically informed NLP
For example, incorporating linguistic structure, compositionality, pragmatics, discourse, multilinguality, or theories of meaning into model architectures, representations, prompting strategies, or training objectives.
Human-centered evaluation and annotation
For example, evaluation methodologies grounded in human communication and cognition; human-informed task design; annotation frameworks derived from linguistic or psycholinguistic theory; communicative grounding; and evaluation beyond benchmark-centric notions of performance.
Language models and the scientific study of language
For example, using NLP models as tools for studying linguistic phenomena, language acquisition, psycholinguistics, discourse, communication, and social interaction; and understanding where current models align with or diverge from human language behavior.
Language, the brain, and neuroscience
For example, computational models of language processing in the brain; neural and behavioral alignment studies; multimodal studies of language understanding; and NLP methods for studying cognition and communication in naturalistic settings.
Language, interaction, and society
For example, conversational alignment, communication in social contexts, language and identity, language and emotion, behavioral modeling through language, and the role of language technologies in human-centered applications.
Foundations of language and meaning
For example, representation of meaning in humans and machines; pragmatics, reference, grounding, ambiguity, context dependence, and philosophical perspectives on language and communication.
This special theme is intended to complement the broad scope of EACL while highlighting the continuing importance of language itself, not merely as large-scale training data, but as a deeply human phenomenon central to communication, cognition, and society. We encourage submissions that combine methodological rigor with broader scientific insight, and that help strengthen the dialogue between NLP and the scientific study of human language.
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