EACL 2027 Industry Track 9-14 March 2027, Athens, Greece Website: https://2027.eacl.org/ Contact: eacl2027-industry-track@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/