VideoRecSys 2023: Large-Scale Video Recommender Systems Workshop
The 1st Workshop on
Large-Scale Video Recommender Systems
At ACM RecSys '23 Sep 19th, 2023
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Invited Speakers


Lukasz Heldt

Mountain View, USA

Thomas Bredillet

New York, USA

Minmin Chen

Google DeepMind
Mountain View, USA

Ko-Jen (Mark) Hsiao

Los Gatos, USA

Qingpeng Cai

Beijing, China


The demand for personalized video recommendations has grown exponentially with the widespread use of video content across various domains, including entertainment, e-commerce, education and social media. The explosive growth of video content on the internet, combined with the ubiquitous availability of high-speed internet and advancements in mobile camera technology have made it easier than ever for users to create, access and consume videos. With the proliferation of online social media applications like Instagram, YouTube, Facebook and TikTok, the need for large-scale video recommendation systems which can provide users with personalized and relevant recommendations has increased.

The Large-Scale Video Recommendations workshop (VideoRecSys) acknowledges the vital significance of these systems and the unique challenges and opportunities they present. With the explosive growth of video platforms and the diverse array of user behaviors and preferences, addressing scalability, diversity and serendipity in recommendations becomes a complex yet vital endeavor.

Join us in this workshop where we bring together renowned researchers and industry experts in the field to delve into the latest advancements, cutting-edge techniques and innovative approaches that are shaping the future of large-scale video recommender systems. Through insightful discussions, engaging presentations and collaborative networking, we aim to foster a deeper understanding of the field's intricacies and collectively chart a course towards more effective, responsible and impactful video recommendations.


Time Talk
14:00-14:15 SGT Opening Remarks [Slides]
14:15-14:45 SGT Keynote: YouTube Discovery Evolution [Slides]
Lukasz Heldt, Google
14:50-15:20 SGT Foundational Models for Long Range Interactions History Modeling [Slides]
Thomas Bredillet, Instagram
15:20-16:05 SGT Coffee Break Networking
16:05-16:35 SGT Intents and Journeys: An LLM Approach [Slides]
Minmin Chen, Google DeepMind
16:35-17:05 SGT From Stranger Things to Your Things: Netflix's Recommendation Evolution [Slides]
Ko-Jen (Mark) Hsiao, Netflix
17:05-17:35 SGT Reinforcement Learning for Short Video Recommender Systems [Slides]
Qingpeng Cai, KuaiShou

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Workshop Organizers


Khushhall Chandra Mahajan

Menlo Park, CA

Amey Porobo Dharwadker

Menlo Park, CA

Saurabh Gupta

Menlo Park, CA

Brad Schumitsch

Menlo Park, CA

Contact us

Please send questions and enquiries to videorecsys [at] gmail [dot] com.