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WASP 2027 : The 5th Workshop on Artificial Intelligence for Scientific Publications | |||||||||||
| Link: https://ui.adsabs.harvard.edu/WIESP/2027/ | |||||||||||
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Call For Papers | |||||||||||
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First CALL FOR PAPERS The 5th Workshop on Artificial Intelligence for Scientific Publications (WASP 2027) Co-located with NAACL 2027 June 1-5, 2027, San Francisco, USA (in person) Website: https://ui.adsabs.harvard.edu/WIESP/2027/ Submissions (OpenReview): TBA ==================================================================== OVERVIEW We are delighted to announce that the 5th edition of the Workshop on Artificial Intelligence for Scientific Publications (WASP 2027) will be held in person at NAACL 2027 in San Francisco. WASP brings together researchers working at the intersection of NLP, machine learning, and the scientific publishing ecosystem, from authoring and peer review to the discovery, extraction, and synthesis of scientific knowledge. The scientific literature now grows faster than anyone can read it, and the claims, evidence, entities, relations, and citations that researchers rely on remain locked in unstructured text. As large language models become deeply embedded in how research is written, reviewed, and read, WASP 2027 invites contributions that advance both the capabilities and the trustworthiness of these systems. This iteration places a sharpened focus on interpretable and explainable scientific reasoning: understanding not just what a system concludes, but why, and whether that conclusion can be trusted and verified, reflected directly in our shared task. WASP continues a series that began as the Workshop on Information Extraction from Scientific Publications (WIESP) at AACL-IJCNLP 2022 and IJCNLP-AACL 2023, grew into WASP at IJCNLP-AACL 2025 and 2026, and now comes to NAACL 2027. TOPICS OF INTEREST (not limited to) - Interpretable and explainable scientific reasoning (the sharpened focus of this iteration): explainable and verifiable hypothesis generation, faithfulness and attribution for scientific claims, uncertainty quantification, and human-in-the-loop evaluation of AI-assisted discovery - The prevalence and impact of AI-generated ("AI slop") content in scientific publications, and its effects on research integrity, quality, and trust - The roles and responsibilities of the different stakeholders (authors, reviewers, editors, publishers, and readers) in an AI-assisted publishing ecosystem - Scientific document parsing and structured information extraction; citation context/span extraction and citation-based knowledge mining - Scientific named-entity recognition and concept identification - Scientific literature quality assessment and automated peer review assistance - Argument extraction and scientific discourse analysis - Scientific article summarisation and headline generation - Question-answering and fact retrieval from scientific literature - Pretraining and fine-tuning LLMs on scientific corpora - Evaluation and alignment of LLMs for scientific understanding - AI-assisted scientific discovery and hypothesis generation - Cross-lingual scientific knowledge transfer and multilingual publication processing - Scientific trend analysis and research gap identification - Reproducibility and replicability analysis in scientific publications - Ethical and responsible use of LLMs in scientific publishing - Automated metadata generation and semantic tagging of scientific publications - Scientific plagiarism detection and research integrity monitoring - Scientific collaboration network analysis and co-authorship prediction - Automated scientific writing assistance and manuscript generation - Scientific image and figure analysis in publications SUBMISSION Long papers: up to 8 pages of content (9 in the camera-ready), plus unlimited references. Short papers: up to 4 pages of content (5 in the camera-ready), plus unlimited references. All submissions are double-blind and must follow the host venue formatting guidelines and ACL template files. We follow NAACL 2027 policies on anonymity, preprints, and double submissions. Accepted papers will appear in the WASP 2027 proceedings in the ACL Anthology. Submit via OpenReview: TBA SHARED TASK WASP 2027 will host a shared task, this year centered on interpretable and explainable scientific reasoning. Details and a separate call for papers will be announced soon. System description papers will undergo light peer review and appear in the proceedings. IMPORTANT DATES (Anywhere on Earth) Paper submission deadline (WASP): February 5, 2027 Registration deadline for shared task: (to be determined) Notification of acceptance (WASP):(to be determined) Camera-ready deadline (WASP + Shared Task): (to be determined) Workshop: June 1-5 (to be determined), 2027 ORGANIZERS - Atilla Kaan Alkan, Center for Astrophysics | Harvard & Smithsonian, USA - Alberto Accomazzi, Center for Astrophysics | Harvard & Smithsonian, USA - Tirthankar Ghosal, Oak Ridge National Laboratory, USA - Felix Grezes, Center for Astrophysics | Harvard & Smithsonian, USA - Kelly Lockhart, Center for Astrophysics | Harvard & Smithsonian, USA CONTACT For inquiries: Atilla Kaan Alkan, atilla.alkan@cfa.harvard.edu We look forward to your contributions. |
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