Call for Papers: EMNLP 2026 Industry Track
Conference: October 24–29, 2026
Location: Budapest, Hungary
Paper submission deadline: June 16, 2026 (11:59 PM UTC-12:00, AoE)
Submission link: TBA
Background
Language technologies are now integral to real-world systems across industries. While many advances originate in controlled research environments, both academic and industrial research laboratories, deploying these technologies in production raises challenges that rarely surface in controlled lab settings. Challenges can include latency and cost constraints, shifting user behaviour, maintenance over time, evaluation without clean test sets, integration with human workflows, and trade-offs between quality and practicality. To provide a forum to address these multifaceted issues, we are seeking submissions that not only dive into research but also demonstrate the application of systems in real-world scenarios, irrespective of whether they involve proprietary data. We invite submissions that describe the design, development, deployment, or analysis of NLP and speech systems in real-world settings.
Topics
We invite submissions describing innovations and implementations in all areas of speech and language technologies for real-world applications. The primary focus of this track is on papers that advance the understanding of, and demonstrate the effective handling of, practical challenges related to the deployment of language processing and generation systems, including those based on large language models, in non-trivial real-world settings. Such real-world systems include applications that are used outside controlled environments such as laboratories, classrooms, or experimental crowdsourcing setups.
Submissions may describe systems that are not necessarily state-of-the-art in terms of research, but that demonstrate meaningful use of NLP and/or speech technologies in practice. We encourage submissions from both non-profit and for-profit sectors, with the understanding that the end-users of these systems extend beyond the NLP community. Submissions are not restricted to industry authors or to proprietary data -- academic work on genuinely deployed systems is equally welcome, as are negative results, lessons learned, and vision papers grounded in deployment experience. Please note that if submissions involve proprietary data, there is no requirement to make this data available. Overall, this track aims to highlight key insights, lessons learned, and emerging research challenges that arise from real-world implementations of language technologies.
Relevant areas include (topics in alphabetical order, including, but not limited to):
A. System design, efficiency, maintainability and scalability of real-world applications
- Benchmarks and methods for latency and efficiency optimisation
- Continuous maintenance and system evolution
- Efficient methods for training and inference
- Implementation at optimised speed, scale and cost
- Infrastructure for large-scale deployment
- Handling unexpected user behaviour
- Human-in-the-loop system design
- Negative results related to real-world applications
- System combination and orchestration
B. Novel applications and use cases
- Best practices and lessons learned
- Case studies, from design to deployment
- Dataset creation for real-world applications
- Description of an application or system
- Development under practical constraints (model or data size)
- Novel applications and novel, previously unsolved problems
C. Methods for deployed systems
- Ethics, bias, fairness, harmlessness and trustworthiness in deployed systems
- Evaluation methodologies (offline and online)
- Interpretability and transparency
- Interactive and user-facing systems
- Online learning and adaptation
- Robustness and reliability
In addition, opinion/vision papers related to real-world applications are also welcome.
Important Dates
| Event | Date |
|---|---|
| Submission Deadline | June 16, 2026 |
| Review Release / Rebuttal Begins | July 30, 2026 |
| Author Response Deadline | August 6, 2026 |
| Notification of Acceptance | August 20, 2026 |
| Camera-ready Deadline | September 20, 2026 |
| Conference | October 24–29, 2026 |
All deadlines are 11.59 pm UTC -12h (anywhere on earth).
Following the ACL Policies for Review and Citation, updated in early 2024, there is no anonymity period requirement, e.g., one may upload the paper to arXiv at any time.
Please note that the EMNLP 2026 Industry Track does not use ARR!
Evaluation and Decision 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 emphasise real-world implementations of NLP 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); in that regard, due to the type of work we expect to be submitted to the Industry Track, we ask authors to pay specific attention to their evaluation methodologies (human vs. automated).
Submission Requirements
Authors are invited to submit original, full-length (maximum of 6 pages) industry track papers that are not previously published, accepted to be published, or under consideration for publication in any other forum. Manuscripts should be submitted electronically, in PDF format and formatted using the templates available here. Please do not modify these style files, nor should you use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be desk-rejected.
Length and appendices: Industry Track papers cannot exceed 6 pages in length (excluding ethical considerations and references). References and limitations sections do not count toward the page limit, nor do the following optional sections: acknowledgements (only in the final version), ethical considerations, and appendices.
After the bibliography, papers can have an optional appendix with, e.g., examples or sample inputs/outputs, pre-processing decisions, model parameters, feature templates, pseudocode, information about user studies, additional error analysis or other details that are necessary for the replication of the work described in the paper. Note, however, that paper submissions must be fully self-contained, i.e., supplementary materials, as provided in the appendix, are completely optional, and reviewers are not even asked to review them. Authors are asked not to abuse the option of an unlimited appendix and only to include material that supports the primary messages and content of the paper; to avoid any misunderstandings regarding the nature of the appendix, for the final papers, especially those with an appendix of excessive length, the EMNLP 2026 Industry Track chairs reserve the right to include a statement that it is not mandatory for reviewers to review the material presented in the appendix.
Supplementary Materials: Authors may submit separate files as supplementary materials, such as software or data.
Limitations: Authors are required to discuss the limitations of their work in a dedicated section titled “Limitations”. This section should be included at the end of the paper, before the references, and it will not count toward the page limit. Papers without a limitations section will be desk rejected.
Double-blind review: Industry Track submissions must neither include the authors’ names nor their affiliations. Self-references that reveal the authors’ identities must be avoided. For example, instead of “We previously showed (Smith, 1991) …” or even “We previously showed (Anonymous, 1991) …”, please use “Smith (1991) previously showed …”. Authors should also be careful not to reveal their affiliation indirectly, for example, through screenshots or trade names. Submissions should avoid links to non-anonymised repositories: code should be submitted as a link to an anonymised repository (e.g., Anonymous GitHub or Anonym Share). Please avoid links to storage services like Dropbox / Google Drive (which may track the reviewers downloading the resources). Papers that do not conform to these requirements will be desk-rejected.
Citation and comparison: Authors are expected to cite all refereed publications relevant to their submission, but may be excused for not knowing about all unpublished work (especially work that has been recently posted and/or is not widely cited). In cases where a preprint has been superseded by a refereed publication, the refereed publication should be cited in addition to or instead of the preprint version. Papers (whether refereed or not) appearing less than 3 months before the submission deadline are considered contemporaneous to a submission, and authors are therefore not obliged to make detailed comparisons that require additional experimentation and/or in-depth analysis. For more information, see the ACL Policies for Review and Citation.
Writing assistance: Overall, the EMNLP 2026 Industry Track adheres to the ACL policy on using writing assistants (including AI-based writing assistants and other AI tools) available here. Moreover, following the new policy of the main EMNLP 2026 conference track, regarding paper integrity, we will take actions against unethical paper submissions that overwhelm community resources, including but not limited to, thinly sliced contributions, submissions with hallucinated citations, and entirely AI-generated papers (AI writing assistance is permitted) as well as submissions that violate the ACL Policy on Publication Ethics. Such submissions may be desk rejected, and all authors involved in the submission may be ineligible to commit their paper(s) to EMNLP 2026 and EMNLP 2027.
Submission system: Papers have to be submitted through the EMNLP 2026 Industry Track online submission system (link TBA).
Final version: Accepted papers will be given one additional page of content (up to 7 pages; ethical considerations, limitations, acknowledgements and references do not count against this limit) so that reviewers’ comments can be taken into account. Previous presentations of the work (e.g., preprints on arXiv.org) should be indicated in a footnote that should be excluded from the review submission, but included in the final version of papers appearing in the EMNLP 2026 proceedings.
The final version should remove anonymisation in text, citation, and figures. For example, the final version may include the names of the authors’ institutions, trademarks, and screenshots of identifiable products. Please notice that once the paper has been submitted, no changes to the list of authors are allowed.
Presentation requirement for accepted papers: Industry Track papers will be presented orally or as posters, to be determined by the program committee. All accepted papers must be presented at the conference (either via online or in-person presence). At least one author of each accepted paper must register for EMNLP 2026 by the early registration deadline. The EMNLP 2026 Industry Track will run in parallel with the Research Track.
Presentation Mode: Accepted papers will be presented orally or as posters, as determined by the program committee. The decisions as to which papers will be presented orally and which as poster presentations will be based on the nature rather than the quality of the work. There will be no distinction in the proceedings between papers presented orally or as posters
Multiple Submission Policy
Multiple Submission Policy
EMNLP 2026 will not consider any paper that is under review in a journal or another conference at the time of submission, and submitted papers must not be submitted elsewhere during the EMNLP 2026 review period. This policy covers all refereed and archival conferences and workshops (e.g., NeurIPS, EMNLP workshops), as well as ARR. In addition, we will not consider any paper that overlaps significantly in content or results with papers that have been (or will be) published elsewhere. Authors submitting more than one paper to EMNLP 2026 must ensure that their submissions do not overlap significantly (>25%) with each other in content or results.
Submissions of identical or closely related work to multiple EMNLP 2026 tracks (e.g., to the research track and industry track) will be treated as duplicate submissions. Such submissions violate our multiple submission policy and will be rejected without review. The authors should also include the papers that their paper overlaps with or extends in the references section as follows: Anonymous Authors, “Title of the paper”, Under submission at EMNLP 2026 (TRACK NAME).
Furthermore, there is a growing risk of multiple submissions from nearly identical groups of co-authors, where the papers cover largely overlapping topics with only minor methodological variations – often facilitated by generative AI tools. In order to address this concern, we are extending and reinforcing our multiple submission policy for the EMNLP 2026 Industry Track as follows: all papers submitted by the same or almost identical group of co-authors will be treated as related prior work. For any such submissions that cover overlapping or closely related topics, the authors must ensure mutual citation between the papers and include discussions of each work within the main body. Additionally, anonymised PDF files of these cited concurrent submissions must be provided in the supplementary materials. Failure to comply with this policy may result in the rejection of all non-compliant submissions.
Ethics Policy
Authors are required to honour the ethical code set out in the ACL Code of Ethics. The consideration of the ethical impact of our research, use of data, and potential applications of our work has always been an important consideration, and as artificial intelligence is becoming more mainstream, these issues are increasingly pertinent. We ask that all authors read the code and ensure that their work conforms to this code. Where a paper may raise ethical issues, we ask that you include in the paper an explicit discussion of these issues, which will be taken into account in the review process. We reserve the right to reject papers on ethical grounds, where the authors are judged to have operated counter to the code of ethics or have inadequately addressed legitimate ethical concerns with their work.
Authors will be allowed extra space after the sixth page for an optional broader impact statement or other discussion of ethics. The EMNLP review form will include a section addressing these issues, and papers flagged for ethical concerns by reviewers or ACs will be further reviewed by an ethics committee. Note that an ethical considerations section is not required, but papers working with sensitive data or on sensitive tasks that do not discuss these issues will not be accepted. Conversely, the mere inclusion of an ethical considerations section does not guarantee acceptance. In addition to acceptance or rejection, papers may receive a conditional acceptance recommendation. Camera-ready versions of papers designated as conditionally accepted will be re-reviewed by the ethics committee to determine whether the concerns have been adequately addressed. Please read the ethics FAQ for more guidance on some problems to look out for and key concerns to consider relative to the code of ethics.
Contact Information
Industry Track Co-Chairs:
Pepa Atanasova (University of Copenhagen)
Gholamreza Haffari (Monash University and Openstream AI)
Email: emnlp2026-industry-track@googlegroups.com
Frequently Asked Questions
Frequently Asked Questions
Is the Industry Track only for participants from industry? No, the Industry Track welcomes participants from the entire ACL community. Researchers working on real-world applications that match the Industry Track call for papers are invited to submit papers. Everyone is welcome to attend Industry Track sessions.
What do you mean by real-world applications? We are looking for applications that are deployed (or expected to be deployed) for real-world use, i.e., outside controlled environments such as laboratories, classrooms or experimental crowd-sourced setups.
Can students also submit papers to the Industry Track? Yes! If your work matches the Industry Track call for papers, consider submitting a paper to the Industry Track.
I work in industry. Can I still submit my paper to the research track? Absolutely! There are no changes to the main conference submissions. The Industry Track offers a forum to submit papers describing aspects of real-world applications that may differ in focus from the research track reviewing criteria.
Will the papers in the Industry Track be published in the proceedings? Yes, Industry Track papers will be published as a separate volume of the proceedings. For example, see the EMNLP 2025 proceedings.
How do I decide whether to submit to the research track or the Industry Track? Papers describing key lessons learned and challenges pertaining to real-world deployment of NLP and speech technologies are best suited for the Industry Track. Authors are advised to review the call for papers for both tracks and submit to the track that best matches their work. The list of topics and reviewing criteria may be helpful. You can also reach out to the track chairs if you need help deciding.