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 5551–5575 of 14297 papers

TitleStatusHype
DINER: Disorder-Invariant Implicit Neural Representation—0
BIMCV-R: A Landmark Dataset for 3D CT Text-Image Retrieval—0
Billion-scale Similarity Search Using a Hybrid Indexing Approach with Advanced Filtering—0
Dimension Projection among Languages based on Pseudo-relevant Documents for Query Translation—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations—0
Advances in 3D scattering tomography of cloud micro-physics—0
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds—0
Dimensionality Detection and Integration of Multiple Data Sources via the GP-LVM—0
Bilingual Topic Models for Comparable Corpora—0
Bilingual Terminology Extraction Using Neural Word Embeddings on Comparable Corpora—0
Mixed-initiative Query Rewriting in Conversational Passage Retrieval—0
Digging Into Self-Supervised Learning of Feature Descriptors—0
Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective—0
DiffusionVMR: Diffusion Model for Joint Video Moment Retrieval and Highlight Detection—0
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
An Experimental Study on Pretraining Transformers from Scratch for IR—0
Advances and Challenges in Conversational Recommender Systems: A Survey—0
A Collaborative Multi-Agent Approach to Retrieval-Augmented Generation Across Diverse Data—0
Diffusion Processes for Retrieval Revisited—0
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines—0
Diffusion Handles Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D—0
An experimental comparison of label selection methods for hierarchical document clusters—0
Diffusion Handles: Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D—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