Media Summary: Zuohui Fu (Rutgers University) Yikun Xian (Rutgers University) Yongfeng Zhang (Rutgers University) Yi Zhang (UC Santa Cruz) Due to strong capabilities in conducting fluent, multi-turn conversations with users, Large Language Models (LLMs) have the ... by Ting Yang (Hong Kong Baptist University) and Li Chen (Hong Kong Baptist University) Abstract:

Recsys 2020 Tutorial Conversational Recommender Systems - Detailed Analysis & Overview

Zuohui Fu (Rutgers University) Yikun Xian (Rutgers University) Yongfeng Zhang (Rutgers University) Yi Zhang (UC Santa Cruz) Due to strong capabilities in conducting fluent, multi-turn conversations with users, Large Language Models (LLMs) have the ... by Ting Yang (Hong Kong Baptist University) and Li Chen (Hong Kong Baptist University) Abstract: Counteracting Bias and Increasing Fairness in Search and Session P7B: Understanding and Modeling Preferences Session Chairs: Michael Ekstrand and Ludovico Boratto ... All right can we see yep okay well welcome everyone to uh workshop on context aware

In this webinar, Krisztian Balog (Professor, University of Stavanger) talks about

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RecSys 2020 Tutorial: Conversational Recommender Systems
RecSys 2020 Tutorial: Feature Engineering for Recommender Systems
Tutorial on Conversational Recommendation Systems
RecSys 2020 Tutorial: Introduction to Bandits in Recommender Systems
Recent Advances in Generative Conversational Recommender Systems
RecSysOps: Best Practices for Operating a Large-Scale Recommender System
A Multi Agent Conversational Recommender System
Unleashing the Retrieval Potential of Large Language Models in Conversational Recommender Systems
Tutorial 1C Conversational Recommender System Using Deep Reinforcement Learning
RecSys 2020 Tutorial: Adversarial Learning for Recommendation
RecSys 2020 Tutorial: Counteracting Bias and Increasing Fairness in Search and Recommender Systems
RecSys 2020 Session P7B: Understanding and Modeling Preferences
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