37.2345, Confs: EACL 2027 Industry Track (Greece)

[The LINGUIST List]

LINGUIST List: Vol-37-2345. Wed Jul 15 2026. ISSN: 1069 - 4875.

Subject: 37.2345, Confs: EACL 2027 Industry Track (Greece)

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Date: 14-Jul-2026
From: Daniel Preotiuc-Pietro [eacl2027-industry-track at googlegroups.com]
Subject: EACL 2027 Industry Track


EACL 2027 Industry Track
Short Title: EACL 2027 IT

Date: 09-Mar-2027 - 14-Mar-2027
Location: Athens, Greece
Meeting URL: https://2027.eacl.org/

Linguistic Field(s): Computational Linguistics

Submission Deadline: 11-Sep-2026

Website: https://2027.eacl.org/
Contact: eacl2027-industry-track at googlegroups.com
Full CfP: https://2027.eacl.org/calls/industry/
Important Dates:
Submission deadline ― 11 September 2026
Reviews released ―  21 October 2026
Rebuttal ends ―  4 November 2026
Meta reviews released ―  30 November 2026
Notification of acceptance ― 18 December 2026
Camera-ready due ―  6 January 2027
Conference (including Industry Track) ― 9-14 March 2027
All deadlines are 11.59pm UTC -12h
Submission website:
https://openreview.net/group?id=eacl.org/EACL/2027/Industry_Track
Background:
Language technologies and their applications are an integral and
critical part of our daily lives. Many of these technologies have
their roots in academic and industrial laboratories where researchers
invented a plethora of algorithms, benchmarked them against shared
datasets and perfected their performance to provide plausible
solutions to real-world applications. While a controlled laboratory
setting is vital for a deeper scientific understanding of the problems
underlying language technologies and the impact of algorithmic design
choices on their performance, transitioning the technology to
real-world industrial strength applications raises a different, yet
challenging, set of technical issues.
The EACL 2027 Industry Track aims to highlight this mutual influence
of language technology in academia and industry, which has
significantly contributed to the proliferation of industry
applications. The track - following the tradition of related industry
track series at EACL, NAACL, ACL and EMNLP - provides the opportunity
for researchers, engineers, practitioners and users to meet and
discuss the latest language technologies methods as deployed in a
real-world setting and aims to be the premier forum for knowledge
sharing across the boundary between academia and industry.
We invite submissions describing innovations and implementations in
all areas of speech and natural language processing technologies and
systems that are relevant to real-word applications. The primary focus
of this track is on papers that advance the understanding of, and
demonstrate the effective handling of, practical issues related to the
deployment of language processing technologies in real-world use
application. We encourage submissions from industry, non-profit,
government, and public-sector organisations, with the understanding
that the end-users of these systems extend beyond the NLP community.
Please note that if submissions involve proprietary data, there is no
requirement to make this data available.
Given the wider scale deployment of language technologies, this year’s
edition particularly welcomes work that addresses the operational
maturity of real-world systems — including longitudinal studies of
systems in production, the evolution of evaluation and testing
practices as deployments shift from deterministic automation toward
ML- and LLM-based components, and experiences with data and model
governance.
Topics:
The EACL 2027 Industry Track provides the opportunity to highlight key
insights and new research challenges that arise from the development
and deployment of real-world applications using language technologies.
Relevant areas include system design, efficiency, maintainability, and
scalability of real-world applications, with topics including but not
limited to:
 - Benchmarks and methods for improving latency and efficiency of
systems, including cost, latency, and efficiency of LLM/LM training
and inference at scale
 - Continuous maintenance and improvement of deployed systems,
including longitudinal studies of AI/NLP systems in production
(performance drift, maintenance burden, and lifecycle management)
 - Enabling infrastructure for large-scale deployment
 - Human-in-the-loop approaches to application development
 - Implementation at speed, scale, or low-cost
 - System combinations
 - Evaluation, testing, and quality-assurance requirements and
procedures for LLM-based components
 - Data and model governance procedures for deployed systems,
including versioning strategies, lineage, access control, auditing,
and compliance
 - Citizen-facing systems and public services, including challenges
from multilingual, procurement and regulatory constraints
Novel applications and use cases, including but not limited to:
 - Best practices, lessons learned, or vision pieces on deploying
real-world applications
 - Case studies, from design to deployment
 - Description of an application or system
 - Design of application-relevant datasets
 - Development of methods under system constraints
 - Novel NLP applications
Methods for deployed systems, including but not limited to:
 - Ethics, bias, fairness, and harmlessness
 - Interactive systems
 - Interpretability
 - Offline/online system evaluation methodologies
 - Online learning
 - Robustness and reliability of systems in production
Evaluation Criteria:
Submissions will be reviewed in a double-blind manner and assessed
based on their novelty, technical quality, potential impact, and
clarity. Submissions to the industry track should emphasize real-world
implementations of natural language processing systems, the
development of such systems, or provide insights based on real-world
datasets with obvious industry impact. For papers that rely heavily on
empirical evaluations, the experimental methods and results should be
clear, well executed, and reproducible (though the data may be
proprietary).
Chairs:
Matthias Gallé ― Poolside
Daniel Preotiuc-Pietro ― Bloomberg
Elena Kochkina ― JPMorganChase
Full CfP is available at: https://2027.eacl.org/calls/industry/



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