Explore a systematic evaluation of neural retrieval models in this 15-minute conference talk presented at SIGIR 2024. Delve into the performance analysis of various neural retrieval models on the Touché 2020 Argument Retrieval subset of BEIR (Benchmark for IR). Gain insights from authors Nandan Thakur, Luiz Bonifacio, Maik Fröbe, Alexander Bondarenko, Ehsan Kamalloo, Martin Potthast, Matthias Hagen, and Jimmy Lin as they discuss their findings and methodologies. Learn about the latest advancements in neural information retrieval and their applications to argument retrieval tasks.
Systematic Evaluation of Neural Retrieval Models on Touché 2020 Argument Retrieval Subset of BEIR
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 T2.3 [rr] Systematic Eval of Neural Ret Mod Touché 2020 Argument Retrieval Subset BEIR
Taught by
Association for Computing Machinery (ACM)
Related Courses
-
Resources for Brewing BEIR - Reproducible Reference Models and Statistical Analyses
-
A Reproducibility Study of PLAID - Neural IR
-
Multi-granular Adversarial Attacks Against Black-box Neural Ranking Models - Lecture 1
-
Axiomatic Causal Interventions for Reverse Engineering Relevance Computation in Neural Retrieval Models - Lecture 3
-
NevIR: Negation in Neural Information Retrieval
-
Steering Large Language Models for Cross-lingual Information Retrieval - Multilingual Retrieval
