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SciProdLLM 2025: 1st Workshop on Human-LLM Collaboration for Ethical
and Responsible Science Production

December 23/24, 2025, Mumbai, India
Co-located with IJCNLP-AACL 2025

https://sciprodllm.github.io/


CALL FOR PAPERS

SciProdLLM 2025 is a forum for presenting and discussing research on integrating large language models (LLMs) into the typical research
workflow: from ideation to experimentation to scientific writing, with
a particular focus on human-centered approaches that ensure ethical
and responsible use of LLMs. We also invite work that evaluates the
quality of LLM-assisted research workflows and the resulting outputs.

We welcome submissions on any aspect of human-LLM collaboration for
science production, evaluation of LLMs for science production, and/or evaluation of LLM-assisted scientific papers. Relevant topics include,
but are not limited to, the following:

- Guiding idea generation through user feedback
- Automated experimentation following the experimental workflow used
by human scientists (e.g., the workflow from data preprocessing to
comparison to baselines)
- Human-curated datasets of scientific papers for fine-tuning LLMs for
generating ideas and paper content (text, figures, tables, etc.)
- Human-LLM co-authored peer reviews (e.g., LLM-assisted peer review
platforms)
- Benchmark datasets for evaluating LLMs on idea generation,
experimentation, multimodal content generation, or scientific
writing
- Evaluation metrics for detecting problematic papers (e.g., those
containing suspicious citations or tortured phrases)
- Statistical analyses of collections of LLM-assisted papers (e.g., on
topics, citations, or retractions)


SUBMISSION INSTRUCTIONS

SciProdLLM 2025 welcomes long and short papers. Long papers may
consist of up to 8 pages of content, plus unlimited pages of
references. Short papers may consist of up to 4 pages of content, plus unlimited pages of references. Both types of submissions must follow
the same requirements and procedures as for IJCNLP-AACL 2025 main
conference papers:
<https://2025.aaclnet.org/calls/main_conference_papers> Note that
papers submitted as non-archival will be allocated presentation time
at the workshop but will not be included in the proceedings.

There are three supported submission modes:

- Direct submissions: Direct submissions will receive up to three
double-blind reviews, and a final decision on acceptance from the
workshop organizers. Direct submissions should be made through the
SciProdLLM page on OpenReview:

<https://openreview.net/group?id=aclweb.org/AACL-IJCNLP/2025/Workshop/SciProdLLM>

- ARR submissions: Unpublished papers that have already been reviewed
and meta-reviewed through ACL Rolling Review may be committed to
SciProdLLM. These papers will not receive new reviews but may be
meta-reviewed by the workshop organizers, who will make a final
decision on acceptance. A commitment link will published in a future
version of this call.

- Previously published papers: We invite non-archival submissions of
papers that have already been recently published elsewhere. This
allows such papers to gain more visibility from the workshop
audience. To submit a previously published paper for presentation,
please email SciProdLLM@groups.io with the details of your paper
(title, authors, abstract, publication venue) and attaching a PDF
copy of the paper. (Submissions of previously published papers need
not adhere to the IJCNLP-AACL 2025 main conference paper policies on
anonymity.)


IMPORTANT DATES

All deadlines are 23:59 UTCreA12 ("Anywhere on Earth").

- September 29, 2025: Submission deadline for direct submissions
- October 27, 2025: ARR commitment deadline
- November 3, 2025: Notification of acceptance
- November 11, 2025: Camera-ready papers due
- December 23 or 24, 2025: Workshop presentations (exact date TBA)


ORGANIZING COMMITTEE

- Wei Zhao, University of Aberdeen, UK
- Jennifer DrCOSouza, TIB Leibniz Information Center for Science and
Technology, Germany
- Steffen Eger, University of Technology Nuremberg, Germany
- Anne Lauscher, University of Hamburg, Germany
- Yufang Hou, IT:U Interdisciplinary Transformation University,
Austria
- Nafise Sadat Moosavi, University of Sheffield, UK
- Tristan Miller, University of Manitoba, Canada
- Chenghua Lin, University of Manchester, UK


CONTACT INFORMATION

Email: SciProdLLM@groups.io
WWW: https://sciprodllm.github.io/
--
Dr. Tristan Miller, Assistant Professor
Department of Computer Science, University of Manitoba https://clam.cs.umanitoba.ca/ | Tel. +1 204 474 6792

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