[DL] [CFP] 12th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems

[Marco Polignano]

*/12th Joint Workshop on Interfaces and Human Decision Making for 
Recommender Systems -/**/IntRS'25
/*https://sites.google.com/view/intrs25/ 
<https://sites.google.com/view/intrs25/>

held in conjunction with the *ACM Conference on Recommender Systems 
(RecSys 2025)*

/Prague, Czech Republic, 22nd-26th September 2025./

*Submission deadline:**July 10th, 2025*

Author notification: *August 6th, 2025*

Camera-ready version: A*ugust 20th, 2025*

*SUBMISSION SITE *

------------------------

https://easychair.org/conferences/?conf=recsys2025workshops

A fundamental challenge in the design of the user interface for 
recommender systems lies in striking the right balance between 
personalization, diversity, and serendipity. While users want 
recommendations aligned with their tastes and past behavior, excessive 
personalization risks creating an echo chamber effect, curtailing 
exploration and discovery. This is where interfaces that offer a range 
of options, unexpected recommendations, and delightful, serendipitous 
finds can make the user experience truly dynamic and rewarding. 
Moreover, the rise of large language models such as GPT, Mistral, and 
LLaMA has pushed recommender systems research into new territory, 
requiring a more comprehensive exploration.

------------------------

TOPICS OF INTEREST INCLUDE, BUT ARE NOT LIMITED TO:

*o User Interfaces*

- Visual interfaces

- Explanation interfaces

- Ethical issues (Fairness and Biases) in explainable interfaces

- Collaborative multi-user interfaces (e.g., for group decision making)

- Spoken and natural language interfaces

- Trust-aware interfaces

- Social interfaces

- Context-aware interfaces

- Ubiquitous and mobile interfaces

- Conversational interfaces

- Example- and demonstration-based interfaces

- New approaches to designing interfaces for recommender systems

- UIs counteracting decision manipulation

- User interfaces and cognitive overload

- Psychological aspects of privacy-aware recommendation interfaces

- Generative AI for recommender systems interfaces

*o Interaction, user modeling, and decision-making*

- Cognitive Modeling for Recommender Systems

- Symbiotic recommender systems

- Explainability of decision-making models

- User-adaptive XAI systems

- Controllability, transparency, and scrutability of decision-making models

- Decision theories and biases (e.g., priming, framing, and decoy effects)

- Detection and avoidance/mitigation of decision biases (e.g., in item 
presentations)

- Preference detection (e.g., eye tracking for automated preference 
detection)

- The role of emotions in recommender systems (e.g., emotion-aware 
recommendation)

- Trust-inspiring UIs (e.g., explanation-aware RSs)

- Argumentation and persuasive recommendation (e.g., aspects of nudging 
in RSs)

- Cultural differences (e.g., culture-aware recommendation)

- Mechanisms for effective group decision making (e.g., group 
recommendation heuristics)

- Decision theories for effective group decision making (e.g., hidden 
profile management)

- Voting Advice Applications

- Human-LLMs interaction, prompting, and chaining

*o Evaluation*

- User-centric evaluation for Symbiotic AI interfaces

- Application descriptions and related case studies in Human-Centered 
Recommender Systems

- Benchmarking platforms for Human-Centered Recommender Systems

- Empirical studies and evaluations of new interfaces

- Empirical studies and evaluations of new interaction designs

- Evaluation methods and metrics (e.g., evaluation questionnaire design)

- Psychological aspects in user-centric evaluation

- Case studies

*PAPER FORMATTING INSTRUCTIONS AND SUBMISSION*

-------------------------------------------

Accepted papers will be included in the workshop proceedings published 
on the CEUR-WS.org site.

We will invite two kinds of submissions, which address novel interface 
issues in recommender systems by following the new CEUR-ART 1 Column 
papers style (https://ceur-ws.org/Vol-XXX/CEURART.zip):

- *Short/Demo papers.* The maximum length is 8 pages (plus up to 2 pages 
of references).

- *Long papers.* The maximum length is 16 pages (plus up to 2 pages of 
references).

Submitted papers will be evaluated according to their originality, 
technical content, style, clarity, and relevance to the workshop.

For short papers, we will encourage alternative modes of presentation 
such as demos, playing out of scenarios, mockups, and alternate media 
such as video.

Demonstration sessions will provide the opportunity to show innovative 
interface designs for recommender systems.

*REGISTRATION*

------------

At least one author of each accepted paper needs to register and attend 
the workshop.

*ORGANIZERS*

----------

Peter Brusilovsky peterb at pitt.edu

/School of Information Sciences, University of Pittsburgh, USA/

//

Alexander Felfernig alexander.felfernig at ist.tugraz.at

/Software Engineering and AI, Graz University of Technology, Austria/

Pasquale Lops pasquale.lops at uniba.it

/Dept. of Computer Science, University of Bari Aldo Moro, Italy/

Marco Polignano marco.polignano at uniba.it

/Dept. of Computer Science, University of BariAldo Moro, Italy/

Giovanni Semeraro giovanni.semeraro at uniba.it

/Dept. of Computer Science, University of Bari Aldo Moro, Italy/

Martijn C. Willemsen - M.C.Willemsen at tue.nl

/Eindhoven University of Technology, The Netherlands/
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