Rethinking InfoNCE: How Many Negative Samples Do You Need?

27 May 2021

Papers citing "Rethinking InfoNCE: How Many Negative Samples Do You Need?"

4 / 4 papers shown

Title
Can LLM-Driven Hard Negative Sampling Empower Collaborative Filtering? Findings and Potentials Chu Zhao Enneng Yang Yuting Liu Jianzhe Zhao G. Guo Xingwei Wang 28 0 0 07 Apr 2025
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making Vivek Myers Chongyi Zheng Anca Dragan Sergey Levine Benjamin Eysenbach OffRL 45 7 0 24 Jun 2024
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion Zijun Long George Killick Lipeng Zhuang Gerardo Aragon Camarasa Zaiqiao Meng R. McCreadie VLM 39 2 0 22 Feb 2024
A Mutual Information Maximization Perspective of Language Representation Learning Lingpeng Kong Cyprien de Masson dÁutume Wang Ling Lei Yu Zihang Dai Dani Yogatama SSL 214 165 0 18 Oct 2019