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 7826–7850 of 14297 papers

TitleStatusHype
SRPCN: Structure Retrieval based Point Completion Network—0
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim VerificationCode0
Reinforcement learning for multi-item retrieval in the puzzle-based storage systemCode0
Classification on Sentence Embeddings for Legal Assistance—0
Pirá: A Bilingual Portuguese-English Dataset for Question-Answering about the OceanCode0
Supervised Contrastive Learning for Product MatchingCode1
Ranking with Confidence for Large Scale Comparison DataCode0
Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing—0
A Survey on Retrieval-Augmented Text Generation—0
Training Semantic Descriptors for Image-Based Localization—0
Language Models Explain Word Reading Times Better Than Empirical Predictability—0
Improving Screening Processes via Calibrated Subset SelectionCode0
TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic MusicCode1
Duplicate Detection in a Knowledge Base with PIKA—0
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning—0
Semantic Annotation and Querying Framework based on Semi-structured Ayurvedic Text—0
Improving BERT-based Query-by-Document Retrieval with Multi-Task Optimization—0
A Privacy-Preserving Image Retrieval Scheme with a Mixture of Plain and EtC Images—0
Learning to Hash Naturally Sorts—0
Learning Super-Features for Image RetrievalCode1
Learning Representations of Entities and Relations—0
A Systematic Literature Review about Idea Mining: The Use of Machine-driven Analytics to Generate Ideas—0
Fair ranking: a critical review, challenges, and future directions—0
Neuro-Symbolic Language Modeling with Automaton-augmented RetrievalCode2
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationCode5
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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