Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback - Lecture 1

Explore a 13-minute conference talk from the Association for Computing Machinery (ACM) that delves into unsupervised large language model alignment for information retrieval using contrastive feedback. Learn about the innovative approach presented by authors Qian Dong, Yiding Liu, Qingyao Ai, Zhijing Wu, Haitao Li, Yiqun Liu, Shuaiqiang Wang, Dawei Yin, and Shaoping Ma. Gain insights into how this method can potentially improve search capabilities and enhance the performance of large language models in information retrieval tasks.

SIGIR 2024 M1.1 [fp] Unsupervised LLM Alignment for Information Retrieval via Contrastive Feedback