Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning

20 June 2024

Papers citing "Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning"

9 / 9 papers shown

Title
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendations Xuansheng Wu Huachi Zhou Yucheng Shi Wenlin Yao Xiao Shi Huang Ninghao Liu LRM 70 11 0 29 Jun 2023
Tuning computer vision models with task rewards André Susano Pinto Alexander Kolesnikov Yuge Shi Lucas Beyer Xiaohua Zhai VLM 44 41 0 16 Feb 2023
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning Pan Lu Liang Qiu Kai-Wei Chang Ying Nian Wu Song-Chun Zhu Tanmay Rajpurohit Peter Clark Ashwin Kalyan ReLM LRM 140 289 0 29 Sep 2022
On component interactions in two-stage recommender systems Jiri Hron K. Krauth Michael I. Jordan Niki Kilbertus CML LRM 53 31 0 28 Jun 2021
SimCSE: Simple Contrastive Learning of Sentence Embeddings Tianyu Gao Xingcheng Yao Danqi Chen AILaw SSL 233 3,371 0 18 Apr 2021
Contrastive Representation Learning: A Framework and Review Phúc H. Lê Khắc Graham Healy Alan F. Smeaton SSL AI4TS 278 705 0 10 Oct 2020
Learning from eXtreme Bandit Feedback Romain Lopez Inderjit S. Dhillon Michael I. Jordan OffRL 79 25 0 27 Sep 2020
ORCAS: 18 Million Clicked Query-Document Pairs for Analyzing Search Nick Craswell Daniel Fernando Campos Bhaskar Mitra Emine Yilmaz B. Billerbeck 43 82 0 09 Jun 2020
Deep Reinforcement Learning in Large Discrete Action Spaces Gabriel Dulac-Arnold Richard Evans H. V. Hasselt P. Sunehag Timothy Lillicrap Jonathan J. Hunt Timothy A. Mann T. Weber T. Degris Ben Coppin OffRL 57 573 0 24 Dec 2015