会议信息

EACL 2027: Conference of the European Chapter of the Association for Computational Linguistics

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截稿日期:
2026-08-03
通知日期:
2026-11-12
会议日期:
2027-03-09
会议地点:
Athens, Greece
届数:
ICORE: A   浏览: 21933   关注: 19   参加: 0

会伴指数 (CP-I)

81.6 / 100
全站第 178 名 / 共 5,693 个会议 · 前 4%

自然语言处理与语音 第 6 / 85

学术认可 (35%)
88
投稿选择性 (20%)
83
会议传承 (20%)
83
社区关注 (10%)
49
资料公开度 (15%)
85

用到的输入: 收录等级：ICORE A · 录用率：26.4%（有记录的 5 届的均值） · 有据可查的届次：21 · 在会伴关注它的研究者：19 人 · 过去 24 个月打开过本页的研究者：13 人

公开资料里还缺: 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 100% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-04

征稿

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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录用率

平均录用率: 25.6% 7 年间 (2006–2023).

年份提交数录用数录用率(%)
2023155048231.1%
2021140032623.3%
201744111927%
20143177824.6%
20123168225.9%
200936010027.8%
20062645219.7%

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