AI4SC @ AAAI 2027
Third AAAI Bridge on Artificial Intelligence for Scholarly Communication
co-located with the 41st Annual AAAI Conference on Artificial Intelligence
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The bridge welcomes multiple types of submissions:
A. Regular research papers which will be published as proceedings.
Long papers: between 10 and 15 pages (excl. references and appendix).
Original research presenting novel methods, models, architectures, reusable resources (dataset, benchmark, knowledge graph, ontologies, evaluation frameworks), theoretical foundations, or empirical findings related to AI in science.
Short papers: between 5 and 9 pages (excl. references and appendix).
Work in progress, position, vision papers, presenting conceptual contributions outlining emerging research directions, proposing new perspectives, discussing open challenges, or advocating for changes in scientific practices, infrastructures, and policies in the age of AI.
Poster/demo papers: below 5 pages (excl. references, no appendix allowed).
Descriptions and demonstrations of AI-powered tools, platforms, prototypes, and infrastructures supporting scientific research, scholarly knowledge management and communication.
B. Non-proceedings submissions to be presented during the bridge and added to the bridge Zenodo community.
Proposed talks: up to 10 pages (excl. references, no appendix allowed).
Contributions to the community: all non-archival, e.g. ideas, previous paper presentation. Presentations of recently published or ongoing work to foster discussion without formal proceedings publication.
Lightning talks abstracts: up to 1 page (excl. references, no appendix allowed).
Brief presentations on any of the aforementioned topics.
We especially encourage researchers to submit their contributions as tutorials including live demonstrations, interactive exercises, or guided practice. We offer allocated time slots of 30 or 60 minutes for your hands-on/demo/interactive workshop during our bridge. Please get in touch with the bridge organisers if you would like your contribution to be allocated one of the slots (ai4sc2027@easychair.org).
All submissions must be prepared using the CEURART style (download, Overleaf template) in English and submitted as a pdf. Authors must include a declaration on the use of generative AI tools (CEUR-WS AI Policy). The bridge proceedings will be submitted for publication at CEUR-WS given sufficient number and length of accepted proceedings papers (category A). Submissions not compliant with CEUR-WS templates and requirements will be desk-rejected.
Submission link: https://easychair.org/conferences/?conf=ai4sc2027
Submission deadline: 3 December 2026 end of the day AoE
Lightning talks abstracts only deadline: 14 January 2027 end of the day AoE
Note that the January deadline is only for category B5! All other contributions have to be submitted until 3 December.
The bridge submissions will undergo a single-blind review process in which at least three members of the program committee will review each submission.
RESEARCH TOPICS
Topics of special relevance for the bridge include, but are not limited to:
Machine Actionable Science
Scientific knowledge extraction from publications, datasets, software, and other scholarly outputs
Scholarly knowledge graphs, ontologies, taxonomies, and semantic representation
Linking, integrating, and aligning scholarly knowledge across disciplines and information sources
Neuro-symbolic AI for scientific knowledge representation, integration, and reasoning
AI-Driven and Automated Scientific Research
Automated and AI-assisted scientific discovery, experimentation, and knowledge generation
AI co-scientists, autonomous research agents, and agentic systems supporting scientific workflows
AI-assisted hypothesis generation, research planning, experimental design, and data analysis
Multi-agent systems for collaborative scientific investigation and problem-solving
AI-assisted literature reviews, systematic reviews, and scientific evidence synthesis
AI-assisted scientific writing, editing, translation, and presentation
AI-supported peer review and research evaluation
Applications of AI across scientific disciplines
Human-AI Collaboration and Research Infrastructure
Human-AI collaboration and interactive scientific workflows
Researcher up-skilling, AI literacy, and the changing roles of researchers
FAIR principles, open research infrastructures, and machine-readable scientific resources
Interoperability and integration of AI tools into existing research environments
Collaborative platforms connecting researchers, AI systems, scholarly resources and research institutions
Interdisciplinary Applications and Impact of AI in Science
Applications of AI in the natural sciences, life sciences, medicine, engineering, social sciences, and humanities
AI for addressing Sustainable Development Goals
Cross-disciplinary knowledge discovery and integration through AI
Case studies demonstrating the adoption, benefits, limitations, and challenges of AI in different research domains
Scientific Alignment and Research Integrity
AI alignment with scientific values, objectives, and research practices
Trustworthy, explainable, transparent, and accountable AI for scientific applications
Hallucination detection, factual verification, and evidence-grounded scientific reasoning
Bias, fairness, uncertainty, and reliability in AI-assisted research
Research integrity, originality, authorship, attribution, and responsible AI use
AI governance, ethical frameworks, policies, and guidelines for scientific research
Human oversight, risk assessment, and safeguards for autonomous scientific system
RESEARCH AREAS
We welcome submissions in the following areas:
Submissions which provide participants with practical skills, tools or detailed knowledge in the use of AI in scientific communication. Experts or experienced professionals in the field are invited to submit tutorials including live demonstrations, interactive exercises, or guided practice.
Submissions which showcase new, high-quality datasets and discuss their structure, methodology, and use. The participants are invited to submit papers describing datasets that have potential value for research, analysis, or application of AI for scholarly communication. These datasets can be new or updated ones. Participants should provide the sources of data, describe how the data was collected, cleaned, structured and potential applications.
Submissions which showcase how systems, frameworks, tools or platforms that have been developed for AI in scientific communication work, their design, and their real-world applications. The participants should submit papers describing fully implemented and functional systems.
The above lists are not exhausting and we welcome submissions on other topics related to the main theme of the Bridge.
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