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 1351–1375 of 14297 papers

TitleStatusHype
A Proposed Large Language Model-Based Smart Search for Archive System—0
Temporal-Aware Spiking Transformer Hashing Based on 3D-DWT—0
Unveiling Temporal Trends in 19th Century Literature: An Information Retrieval Approach—0
3DCoMPaT200: Language-Grounded Compositional Understanding of Parts and Materials of 3D ShapesCode1
SCOT: Self-Supervised Contrastive Pretraining For Zero-Shot Compositional Retrieval—0
MiniRAG: Towards Extremely Simple Retrieval-Augmented GenerationCode5
Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech SynthesisCode1
ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting—0
First Token Probability Guided RAG for Telecom Question Answering—0
VideoRAG: Retrieval-Augmented Generation over Video CorpusCode2
BioAgents: Democratizing Bioinformatics Analysis with Multi-Agent Systems—0
Text2Playlist: Generating Personalized Playlists from Text on DeezerCode0
Deep Reversible Consistency Learning for Cross-modal RetrievalCode0
LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large ContextsCode0
SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue ResolutionCode1
Biomedical Relation Extraction via Adaptive Document-Relation Cross-Mapping and Concept Unique Identifier—0
SUGAR: Leveraging Contextual Confidence for Smarter Retrieval—0
Search-o1: Agentic Search-Enhanced Large Reasoning ModelsCode5
A General Retrieval-Augmented Generation Framework for Multimodal Case-Based Reasoning Applications—0
A Flexible and Scalable Framework for Video Moment SearchCode1
Finding Needles in Emb(a)dding Haystacks: Legal Document Retrieval via Bagging and SVR EnsemblesCode0
Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization—0
Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring ContextsCode0
Reproducing HotFlip for Corpus Poisoning Attacks in Dense RetrievalCode0
Multi-task retriever fine-tuning for domain-specific and efficient RAG—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