Call for Papers: ACL 2026 Industry Track

[ACL Announcements]

Call for Papers: ACL 2026 Industry Track

ACL 2026 Industry Track in San Diego, CA, United States

Conference: July 2 - 7, 2026

Paper submission deadline: February 14, 2026

BACKGROUNDPERMALINK

Language technologies are an integral and critical part of our daily
lives. Many of these applications have their roots in academic and
industrial research 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.

We acknowledge the challenges when adapting language technologies for
building novel and robust real-world applications as the journey from
theoretical research to practical deployment can be difficult.
Challenges can include technical aspects of system deployment and
optimizing for efficiency, making informed design choices or
methodological considerations of incorporating human feedback,
evaluation and oversight. 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.

TOPICSPERMALINK

We invite submissions describing innovations and implementations in all
areas of speech and natural language processing (NLP) 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 or language generation technologies,
including those of large language models, in non-trivial real-world
systems, meaning: applications deployed for real-world use, i.e.,
outside controlled environments such as laboratories, classrooms or
experimental crowd-sourced setups, also including applications that use
NLP and/or speech technology, even if not state of the art in terms of
research. There is no requirement that the system be made by a
for-profit company, but the users of the system are most likely outside
the NLP research community.

This track provides an opportunity to highlight the key insights and new
research challenges that arise from real world implementations.

Relevant areas include:

A. System design, efficiency, maintainability and scalability of
real-world applications, with topics in alphabetical order including,
but not limited to:

* Benchmarks and methods for improving the latency and efficiency of
systems
* Continuous maintenance and improvement of deployed systems
* Efficient methods for training and inference
* Enabling infrastructure for large-scale deployment
* Handling unexpected user behaviour
* Human-in-the-Loop approaches to application development
* Implementation at speed, scale and low-cost
* Negative results related to real-world applications
* System combination

B. Novel applications and use cases, with topics in alphabetical order
including, but not limited to:

* Best practices and lessons learned
* Case studies, from design to deployment
* Description of an application or system
* Design of application-relevant datasets
* Development of methods under system constraints (model or data size)
* Novel, previously unsolved NLP problems and novel NLP applications

C. Methods for deployed systems, with topics in alphabetical order
including, but not limited to:

* Ethics, bias, fairness, harmlessness and trustworthiness in deployed
systems
* Interpretability
* Interactive systems
* Offline and online system evaluation methodologies
* Online learning
* Robustness

In addition, opinion/vision papers related to real-world applications
are also welcome.

Submissions must clearly identify one of the following three areas they
fall into:

*

_Deployed_: Must describe a system that solves a non-trivial real-world
problem. The focus may include describing the problem related to actual
use cases, its significance (against opportunity size, value
proposition, and ideal end state), design/formulation of methods,
tradeoff design decision for solutions, deployment challenges, and
lessons learned.
*

_Emerging_: Must describe the development of a system that solves a
non-trivial real-world problem (it need not be deployed or even close,
but there needs to be evidence that this development is intended for
real-world deployment). Papers that describe enabling infrastructure for
large-scale deployment of NLP techniques also fall in this category.
*

_Discovery_: Must include results obtained from NLP applications in
real-world scenarios that result in actionable insights. These
discoveries should reveal promising directions in their application
areas, leading to further system or societal enhancements. For example,
an actionable discovery from an analysis of call center transcripts may
reveal that certain language choices negatively impact customer
experience, leading to better training of service representatives and
improved customer experience.

IMPORTANT DATESPERMALINK

Paper submission deadline
February 14, 2026

Author response deadline
March 29, 2026

Notification of acceptance
April 12, 2026

Camera-ready deadline
April 19, 2026

Main conference
July 2-7, 2026

All deadlines are 11.59 pm UTC -12h (anywhere on earth).

Following the ACL and ARR 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 ACL 2026 Industry Track does not use ARR!

EVALUATION AND DECISION CRITERIAPERMALINK

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 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 REQUIREMENTSPERMALINK

Authors are invited to submit original, full-length (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 digitally, in PDF format and formatted
using the ACL 2026 formatting requirements. 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). 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 errors 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. Note that it will not be
possible to submit additional separate files as supplementary materials.
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 ACL 2026 Industry Track chairs reserve the right
to include a statement that it was not mandatory for reviewers to review
the material presented in the appendix.

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-anonymized repositories: code should be
submitted as a link to an anonymized repository (e.g., Anonymous GitHub
or Anonym Share). Please avoid links to storage services like Dropbox
(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: The ACL 2026 Industry Track adheres to the ACL
policy on using writing assistants (including AI-based writing
assistants and other AI tools) available here.

Submission system: Papers have to be submitted through the ACL 2026
Industry Track online submission system. The submission link will be
provided soon.

Final version: Accepted papers will be given one additional page of
content (up to 7 pages; ethical considerations, 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 ACL 2026 proceedings.

The final version should remove anonymization in text, citation, and
figures. For example, the final version may include the name 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 onsite presence). At least one author of each
accepted paper must register for ACL 2026 by the early registration
deadline. The ACL 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

Authorship: The author list for submissions should include all (and
only) individuals who made substantial contributions to the work
presented. Each author listed on a submission to the ACL 2026 Industry
Track will be notified of submissions and the final decision. No changes
to the order or composition of authorship may be made to submissions to
the ACL 2026 Industry Track after the paper submission deadline

MULTIPLE SUBMISSION POLICYPERMALINK

ACL 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 ACL 2026 review period. This
policy covers all refereed and archival conferences and workshops (e.g.,
NeurIPS, ACL 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 ACL 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 ACL 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 ACL 2026 (TRACK NAME)_.

ETHICS POLICYPERMALINK

Authors are required to honor 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 is conformant 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 ACL 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 conditional accept 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 INFORMATIONPERMALINK

Industry Track Co-Chairs:

* Yunyao Li (Adobe)
* Georg Rehm (DFKI GmbH)
* Mei Tu (Samsung)

Email: acl-2026-in...@googlegroups.com

General Chair: Philipp Koehn (Johns Hopkins University)