Explore cutting-edge research on leveraging large language models for cross-lingual information retrieval in this 16-minute conference talk from SIGIR 2024. Delve into the innovative approaches presented by authors Ping Guo, Yue Hu, Yanan Cao, Yubing Ren, Heyan Huang, and Yunpeng Li as they discuss strategies for steering these powerful models to enhance multilingual retrieval capabilities. Gain insights into the latest advancements in natural language processing and information retrieval techniques that bridge language barriers and improve search efficiency across diverse linguistic landscapes.
Steering Large Language Models for Cross-lingual Information Retrieval - Multilingual Retrieval
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 M2.4 [fp] Steering Large Language Models for Cross-lingual Information Retrieval
Taught by
Association for Computing Machinery (ACM)
Related Courses
-
Implementing Multilingual Generative AI Cross-lingual RAGs
-
Large Language Models with Semantic Search
-
Multilingual Meta-Distillation Alignment for Semantic Retrieval - Session M2.4
-
Finetuning Large Language Models
-
Retrieval Augmented Generation (RAG) with LangChain
-
Introducing Large Language Models Course (How To)
