SOTAVerified

Retrieval

A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.

Papers

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Showing 6826–6850 of 14297 papers

TitleStatusHype
"Is this an example image?" -- Predicting the Relative Abstractness Level of Image and Text—0
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation—0
Exploiting CLIP-based Multi-modal Approach for Artwork Classification and Retrieval—0
Low-Rank Phase Retrieval via Variational Bayesian Learning—0
Iteratively Improving Biomedical Entity Linking and Event Extraction via Hard Expectation-Maximization—0
Exploiting Citation Knowledge in Personalised Recommendation of Recent Scientific Publications—0
LProtector: An LLM-driven Vulnerability Detection System—0
Iterative Refinement of Project-Level Code Context for Precise Code Generation with Compiler Feedback—0
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match—0
Exploiting Bilingual Translation for Question Retrieval in Community-Based Question Answering—0
CLIP-GCD: Simple Language Guided Generalized Category Discovery—0
IterKey: Iterative Keyword Generation with LLMs for Enhanced Retrieval Augmented Generation—0
It's About Time: Incorporating Temporality in Retrieval Augmented Language Models—0
A Riemannian Framework for Analysis of Human Body Surface—0
It's High Time: A Survey of Temporal Information Retrieval and Question Answering—0
It's Time for Artistic Correspondence in Music and Video—0
Deep Contextualized Biomedical Abbreviation Expansion—0
ITTC @ TREC 2021 Clinical Trials Track—0
I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion—0
Towards Better Monolingual Japanese Retrievers with Multi-Vector Models—0
JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resources—0
Explanations for CommonsenseQA: New Dataset and Models—0
CLIP for All Things Zero-Shot Sketch-Based Image Retrieval, Fine-Grained or Not—0
100,000 Podcasts: A Spoken English Document Corpus—0
Large Language Models Can Be Used to Estimate the Latent Positions of Politicians—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second183.53—Unverified
2ElasticsearchQueries per second21.8—Unverified
3BM25-PTQueries per second6.49—Unverified
4Rank-BM25Queries per second1.18—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second20.88—Unverified
2ElasticsearchQueries per second7.11—Unverified
3Rank-BM25Queries per second0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second41.85—Unverified
2ElasticsearchQueries per second12.16—Unverified
3Rank-BM25Queries per second0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FLMRRecall@589.32—Unverified
2RA-VQARecall@582.84—Unverified
#ModelMetricClaimedVerifiedStatus
1PreFLMRRecall@562.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-KIStext-to-video Mean Rank30—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4OutfitRecall@57.59—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1—Unverified
#ModelMetricClaimedVerifiedStatus
1COLTCOMP@84.55—Unverified
#ModelMetricClaimedVerifiedStatus
1hello0L1,121,222—Unverified