RecSys 2026 Workshop on Online and Adaptive Recommender Systems (OARS)

Call For Papers
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RecSys OARS is a half day workshop taking place on September 28, 2026 in conjunction with RecSys 2026 in Minneapolis, Minnesota, USA.

Workshop website: https://oars-workshop.github.io/
Important Dates:
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- Call for Papers publication: April 21, 2026
- Submissions Due - July 20, 2026
- Notification - August 14, 2026
- Camera Ready Version of Papers Due - August 28, 2026
- Workshop Day - September 28, 2026

Details:
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The international workshop on Online and Adaptive Recommender Systems (OARS) will serve as a platform for publication and discussion of OARS. It will bring together practitioners and researchers from academia and industry to discuss the challenges and new approaches to implement OARS algorithms/systems and improve user experiences by better modeling and responding to user intent.

We invite submission of papers and posters, representing original research, new position and opinion, preliminary results, proposals for new tools, datasets, and resources. All submitted papers will be double-blind and will be peer reviewed by an international program committee of researchers of high repute. Accepted submissions will be presented at the workshop.

Topics of interest include, but are not limited to:
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Agentic recommender systems, assistant-style interfaces, memory and tool-use (2026 special theme)
LLMs and foundation models in RecSys: semantic IDs, tokenization, multi-modality, in-context learning
Online and continual learning, reinforcement learning, bandits, and counterfactual evaluation
Real-time user intent modeling, session-aware and conversational recommendation
Cold-start, distribution shift, and robustness under data sparsity
Predictive analytics and causal inference for recommendation
New architectures: RAG-based, streaming and event-driven, scalable learning
Evaluation, explanation, and off-policy methods for OARS
Privacy, ethics, fairness, and user welfare in OARS
Industry deployments, infrastructure, and real-world case studies

Submission Instructions:
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All papers will be peer reviewed by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion.

All submissions must be formatted according to the ACM Conference Proceeding templates (two column format).

Submissions must describe work that is not previously published, not accepted for publication elsewhere, and not currently under review elsewhere. All submissions must be in English.

Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper in-person.

Submissions to RecSys OARS workshop should be made to the track of “Online and Adaptive Recommender System” at https://easychair.org/my/conference?conf=recsys2026workshops

ORGANIZERS:
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Xiquan Cui Workday, USA
Derek Zhiyuan Cheng Google, USA
Fei Liu Emory University, USA
Tao Ye Lyft, USA
Julian McAuley UCSD, USA
Vachik Dave Walmart Labs, USA
Stephen Guo Indeed, USA

Contact: Please direct all your queries to xiquan.cui@workday.com for help.