[2° CFP] IntRS'26: 13th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems

**

*13th Joint Workshop on Interfaces and Human Decision Making for 
Recommender Systems - IntRS'26*
https://sites.google.com/view/intrs26/ 
<https://sites.google.com/view/intrs26/>

Held in conjunction with the *20th ACM Conference on Recommender Systems*

/Minneapolis, Minnesota, USA, September 28–October 2 2026
/https://recsys.acm.org/recsys26 <https://recsys.acm.org/recsys26>//

**

### *Important Dates *###

*Submission deadline: *July 20, 2026

*Author notification: *August 14, 2026**

*Camera-ready version: *August 28, 2026

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

*Submission Site: 
*https://easychair.org/conferences/?conf=recsys2026workshops 
<https://easychair.org/conferences/?conf=recsys2026workshops>

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

Research on Human-AI collaboration involves several critical areas of 
investigation, such as Human-in-the-loop, Symbiotic AI, Explainable AI, 
User-centered design, and Intelligent Interfaces. Overall, this area of 
research is aimed at developing systems that can work effectively with 
human users, considering their preferences, cognitive abilities, and 
ethical values. They should be transparent, interpretable, adaptable, 
and respectful of the user’s autonomy and privacy. The ultimate goal is 
to develop recommender systems that can support the user’s 
decision-making process, enhance their well-being, and promote social 
good. This means respecting cultural, social, and individual differences 
when crafting recommendations. Inclusive design translates to 
recommendations that truly represent the diverse individuals who use 
these systems. Human-AI collaboration and Human-Centered AI are pivotal 
in the development of recommender systems.

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

### *Topic of Interest *###

Topics of interest include, but are not limited to:

*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

*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 of decision biases (e.g., in item presentations)

§Preference elicitation and construction

§The role of emotions in recommender systems

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

§Argumentation & persuasive recommendation (e.g., aspects of nudging in RSs)

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

§Mechanisms for effective group decision-making

§Decision theories for effective group decision-making

§Voting Advice Applications

§Human-LLMs interaction, prompting, and chaining


*Evaluation*

§User-centric evaluation for Symbiotic AI interfaces

§Application descriptions 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

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

### *Contributions *###

IntRS’26 welcomes submissions that fall in the following three major 
categorizations:

1.*Research Papers*: should present original work that has not been 
previously published, is not under review, and will not be submitted 
elsewhere during the review process.

§*Long *(10 or more "standard" pages, including references) should make 
a clear and novel contribution and be positioned with respect to the 
state of the art.

§*Short *(5-9 "standard" pages, including references) may present 
early-stage research, promising ideas, negative results, or 
thought-provoking perspectives that can stimulate discussion and future 
work.

2.*Reproducibility and Resource Papers*: this category includes 
submissions focused on tools, datasets, benchmarks, and reproducibility 
studies, including newly developed resources, significant updates to 
existing tools, or systematic evaluations of published work.

§*Long *(10 or more "standard" pages, including references) should 
present substantial contributions, such as comprehensive tools, 
large-scale datasets, or in-depth reproducibility analyses.

§*Short *(5-9 "standard" pages, including references) may describe 
smaller-scale resources, focused tool descriptions, or preliminary 
reproducibility efforts of interest to the community.

3.*Position Papers*: are intended for short, critical, or visionary 
contributions that highlight future directions, emerging challenges, or 
reflective perspectives on the field. Position papers may be *up to 4 
pages*, *including references*, and should aim to spark discussion and 
inspire future research, even in the absence of experimental results.

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

### *Submission *###

All submissions must be written in English, formatted as PDF files, and 
follow the *CEUR-WS single-column conference format*, available as a 
compressed archive <http://ceur-ws.org/Vol-XXX/CEURART.zip> and an 
Overleaf template 
<https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/hpvjjzhjxzjk>.

Submissions will undergo a *double-blind peer review process*. Review 
criteria include relevance to the workshop, originality, significance of 
the contribution, technical soundness, clarity of presentation, quality 
of references, and reproducibility.
Authors are encouraged to share code and supplementary material via an 
anonymous repository, such as https://anonymous.4open.science/ 
<https://anonymous.4open.science/>, to support reproducibility.

Submissions that *are not properly anonymized*, fail to follow the 
required formatting, or disregard these guidelines may be rejected 
without review.


Accepted *long and short papers will be published in the CEUR Workshop 
Proceedings* and presented in the main workshop program. Position papers 
will not be included in the published proceedings, but a selection of 
these may be invited for oral presentations.

Please note that *at least one author of each accepted paper must 
register for and attend the workshop in order to present the work. *We 
expect authors, reviewers, and organizers to adhere to the *ACM Conflict 
of Interest Policy* and the *ACM Code of Ethics and Professional Conduct*.

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


### *Organizers *###

*Peter Brusilovsky,*[email protected]

School of Information Sciences, University of Pittsburgh, USA

*Marco de Gemmis,*[email protected]
Dept. of Computer Science, University of Bari Aldo Moro, Italy

*Alexander Felfernig*, [email protected]

Software Engineering and AI, Graz University of Technology, Austria

*Pasquale Lops*, [email protected]

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

*Marco Polignano*, [email protected]

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

*Giovanni Semeraro*, [email protected]

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

*Martijn C. Willemsen*, [email protected]

Eindhoven University of Technology, The Netherlands**


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