Negative Sampling Techniques for Dense Passage Retrieval in a Multilingual Setting - Lecture 4
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore negative sampling techniques for dense passage retrieval in multilingual settings through this 14-minute conference talk presented at SIGIR 2024. Delve into the research conducted by Thilina Rajapakse, Andrew Yates, and Maarten de Rijke as they discuss innovative approaches to improve information retrieval across multiple languages. Gain insights into the challenges and solutions associated with multilingual dense passage retrieval, and learn how negative sampling techniques can enhance the performance of retrieval systems in diverse linguistic contexts.
Syllabus
SIGIR 2024 M2.4 [rr] Negative Sampling Techniques for Dense Passage Retrieval in a Multilingual Set
Taught by
Association for Computing Machinery (ACM)
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent