Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

In-Context Learning: How to Stop Worrying and Love Applied Information Retrieval - Lecture 1

Association for Computing Machinery (ACM) via YouTube

Overview

Explore a thought-provoking conference talk from SIGIR 2024 that delves into the concept of "In-Context Learning" and its implications for Applied Information Retrieval. Presented by authors Debasis Ganguly, Manish Chandra, and Andrew Parry, this 13-minute session examines the intersection of Large Language Models (LLMs) and search technologies. Gain insights into how in-context learning is reshaping the field of information retrieval and discover why embracing these advancements can lead to innovative solutions in search applications. Learn about the potential benefits and challenges of integrating LLMs with traditional search methods, and understand how this fusion is transforming the landscape of applied information retrieval.

Syllabus

SIGIR 2024 M1.1 [pp] "In-Context Learning" How to stop worrying & love Applied Information Retrieval

Taught by

Association for Computing Machinery (ACM)

Reviews

Start your review of In-Context Learning: How to Stop Worrying and Love Applied Information Retrieval - Lecture 1

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.