Call for papers

Researchers are invited to submit unpublished original research on all aspects of Artificial Intelligence and Machine Learning. Additionally, high-quality research results already published in international AI/ML conference proceedings or journals are also welcome for presentation at the conference, and will be published as extended abstracts. Four types of submissions are invited: 

• Regular Papers (Type A): Papers presenting original work that advances Artificial Intelligence and Machine Learning. Position and review papers are also welcome. These contributions should address a well- developed body of research, an important new area, or a promising new topic, and provide a big picture view. Type A papers can be long (up to 15 pages, excluding references and appendices) or short (at most 10 pages, excluding references and appendices). Contributions will be reviewed on the basis of their overall quality and relevance. 
• Encore Abstracts (Type B): Abstracts of work published (or accepted) in an international conference or journal relating to AI/ML and closely related fields. These should have been accepted on or after 1st September 2024. Authors are invited to submit their version of their officially published paper together with an abstract of at most 2 pages (excluding references). Authors are encouraged to include further results obtained after the publication in their abstract and presentation. Submissions will be judged based on their relevance to the conference. Authors may submit at most one type B paper of which they are the corresponding author. 
• Video/Demonstration Abstracts (Type C): Submissions in this category consist of a 5-minute video explaining or demonstrating an AI-related contribution.  Submissions in this category should be accompanied by a 2-page (excluding references) abstract. Accepted submissions may either have their video shown or present a live demonstration at the event. For live demos, any requirements should be mentioned in the submission. Submissions will be evaluated based on their originality and innovative character, the technology deployed, the purpose of the systems in interaction with users and/or other systems, and their economic and/or societal potential. 
• Thesis Abstracts (Type D): Bachelor's and Master's students are invited to submit a 2-page abstract (excluding references) of their completed AI/ML-related thesis. Supervisors should be listed. The thesis should have been accepted on or after 1st September 2024. Submissions will be judged based on their originality and relevance to the conference. 

• Late Breaking Abstracts (Type E): Original and ongoing AI/ML-related work can be submitted as a Late Breaking abstract of 2 pages (excluding references). These late-breaking abstracts will not be selected for oral presentations. 

   

   

  Reviews will be single-blind. All submissions should include the authors' names and their affiliations. All contributions should be written in English, using the Springer CCIS/LNCS format and submitted electronically through OpenReview. Submission implies the willingness of at least one author to register for BNAIC/BeNeLearn 2026 and present in person at the conference.

   

Type A, B and D papers can be accepted for either oral or poster presentation. There will be prizes for the best paper (type A), best demonstration (type C), and best bachelor's or master's thesis (type D). 

Accepted contributions will be included in the conference pre-proceedings, published open access in the form of CEUR workshop proceedings. Similar to previous years, we plan to organize post-proceedings in the Springer CCIS series. A selection of type A papers will be invited to submit to the post-proceedings. 

We invite contributions on any topic in the broad area of Artificial Intelligence and Machine Learning. In addition to fundamental work we encourage cross-domain and interdisciplinary work, as well as application of AI or ML-based techniques. A list of topics includes (not limited):