Four days left to submit to RecSys 2026 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems - IntRS'26

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

Held in conjunction with the 20th ACM Conference on Recommender Systems
Minneapolis, Minnesota, USA, September 28=96October 2 2026
https://recsys.acm.org/recsys26

### Important Dates ###
Submission deadline: July 25, 2026 - AoE time zone
Author notification: August 14, 2026
Camera-ready version: August 28, 2026
------------------------------
Submission Site: https://easychair.org/conferences/?conf=3Drecsys2026worksh=
ops

------------------------------
Research on Human-AI collaboration involves several critical areas of inves=
tigation, such as Human-in-the-loop, Symbiotic AI, Explainable AI, User-cen=
tered design, and Intelligent Interfaces. Overall, this area of research is=
 aimed at developing systems that can work effectively with human users, co=
nsidering their preferences, cognitive abilities, and ethical values. They =
should be transparent, interpretable, adaptable, and respectful of the user=
=92s autonomy and privacy. The ultimate goal is to develop recommender syst=
ems that can support the user=92s decision-making process, enhance their we=
ll-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 piv=
otal in the development of recommender systems.
------------------------------

### Topic of Interest ###

Topics of interest include, but are not limited to:

User Interfaces

=95 Visual interfaces

=95 Explanation interfaces

=95 Ethical issues (Fairness and Biases) in explainable interfaces

=95 Collaborative multi-user interfaces (e.g., for group decision-making)

=95 Spoken and natural language interfaces

=95 Trust-aware interfaces

=95 Social interfaces

=95 Context-aware interfaces

=95 Ubiquitous and mobile interfaces

=95 Conversational interfaces

=95 Example- and demonstration-based interfaces

=95 New approaches to designing interfaces for recommender systems

=95 UIs counteracting decision manipulation

=95 User interfaces and cognitive overload

=95 Psychological aspects of privacy-aware recommendation interfaces

=95 Generative AI for Recommender Systems interfaces

Interaction, user modeling, and decision-making

=95 Cognitive Modeling for Recommender Systems

=95 Symbiotic recommender systems

=95 Explainability of decision-making models

=95 User-adaptive XAI systems

=95 Controllability, transparency, and scrutability of decision-making mode=
ls

=95 Decision theories and biases (e.g., priming, framing, and decoy effects=
)

=95 Detection and avoidance of decision biases (e.g., in item presentations=
)

=95 Preference elicitation and construction

=95 The role of emotions in recommender systems

=95 Trust inspiring UIs (e.g., explanation-aware RSs)

=95 Argumentation & persuasive recommendation (e.g., aspects of nudging in =
RSs)

=95 Cultural differences (e.g., culture-aware recommendation)

=95 Mechanisms for effective group decision-making

=95 Decision theories for effective group decision-making

=95 Voting Advice Applications

=95 Human-LLMs interaction, prompting, and chaining

Evaluation

=95 User-centric evaluation for Symbiotic AI interfaces

=95 Application descriptions in Human-Centered Recommender Systems

=95 Benchmarking platforms for Human-Centered Recommender Systems

=95 Empirical studies and evaluations of new interfaces

=95 Empirical studies and evaluations of new interaction designs

=95 Evaluation methods and metrics (e.g., evaluation questionnaire design)

=95 Psychological aspects in user-centric evaluation

=95 Case studies
------------------------------

### Contributions ###

IntRS=9226 welcomes submissions that fall in the following three major cate=
gorizations:


1.    Research Papers: should present original work that has not been previ=
ously published, is not under review, and will not be submitted elsewhere d=
uring the review process.

=95   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.

=95   Short (5-9 "standard" pages, including references) may present early-=
stage research, promising ideas, negative results, or thought-provoking per=
spectives that can stimulate discussion and future work.


2.    Reproducibility and Resource Papers: this category includes submissio=
ns focused on tools, datasets, benchmarks, and reproducibility studies, inc=
luding newly developed resources, significant updates to existing tools, or=
 systematic evaluations of published work.

=95   Long (10 or more "standard" pages, including references) should prese=
nt substantial contributions, such as comprehensive tools, large-scale data=
sets, or in-depth reproducibility analyses.

=95   Short (5-9 "standard" pages, including references) may describe small=
er-scale resources, focused tool descriptions, or preliminary reproducibili=
ty efforts of interest to the community.


3.    Position Papers: are intended for short, critical, or visionary contr=
ibutions that highlight future directions, emerging challenges, or reflecti=
ve perspectives on the field. Position papers may be up to 4 pages, includi=
ng references, and should aim to spark discussion and inspire future resear=
ch, even in the absence of experimental results.
------------------------------

### Submission ###

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

Submissions will undergo a double-blind peer review process. Review criteri=
a include relevance to the workshop, originality, significance of the contr=
ibution, technical soundness, clarity of presentation, quality of reference=
s, and reproducibility.
Authors are encouraged to share code and supplementary material via an anon=
ymous repository, such as https://anonymous.4open.science/, to support repr=
oducibility.

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

Accepted long and short papers will be published in the CEUR Workshop Proce=
edings 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 f=
or 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]<mailto:[email protected]>
School of Information Sciences, University of Pittsburgh, USA

Marco de Gemmis, [email protected]<mailto:[email protected]>
Dept. of Computer Science, University of Bari Aldo Moro, Italy

Alexander Felfernig, [email protected]<mailto:alexander.fel=
[email protected]>
Software Engineering and AI, Graz University of Technology, Austria

Pasquale Lops, [email protected]<mailto:[email protected]>
Dept. of Computer Science, University of Bari Aldo Moro, Italy

Marco Polignano, [email protected]<mailto:[email protected]>
Dept. of Computer Science, University of Bari Aldo Moro, Italy

Giovanni Semeraro, [email protected]<mailto:giovanni.semeraro@unib=
a.it>
Dept. of Computer Science, University of Bari Aldo Moro, Italy

Martijn C. Willemsen, [email protected]<mailto:[email protected]>
Eindhoven University of Technology, The Netherlands





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