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 3526–3550 of 14297 papers

TitleStatusHype
BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering—0
Data Management Challenges for Internet-scale 3D Search Engines—0
Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2.5 estimations, a study on Tehran—0
AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environments—0
Deep Metric Learning Network using Proxies for Chromosome Classification in Karyotyping Test—0
Deep Metric Learning using Similarities from Nonlinear Rank Approximations—0
Phase-based Minimalist Parsing and complexity in non-local dependencies—0
Deep Metric Learning via Adaptive Learnable Assessment—0
BeatDance: A Beat-Based Model-Agnostic Contrastive Learning Framework for Music-Dance Retrieval—0
Data leakage in cross-modal retrieval training: A case study—0
Deep Metric Learning with Alternating Projections onto Feasible Sets—0
Beef up mmWave Dense Cellular Networks with D2D-Assisted Cooperative Edge Caching—0
Deep Metric Learning with Hierarchical Triplet Loss—0
Deep Metric Learning with Soft Orthogonal Proxies—0
Deep Metric Multi-View Hashing for Multimedia Retrieval—0
Deep Metric Structured Learning For Facial Expression Recognition—0
Deep Models for Multi-View 3D Object Recognition: A Review—0
Data Infrastructure and Approaches for Ontology-Based Drug Repurposing—0
Automating Legal Concept Interpretation with LLMs: Retrieval, Generation, and Evaluation—0
Deep multi-modal networks for book genre classification based on its cover—0
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets—0
Deep Multi-View Enhancement Hashing for Image Retrieval—0
Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering—0
Automating Horizon Scanning in Future Studies—0
Accommodate Knowledge Conflicts in Retrieval-augmented LLMs: Towards Reliable Response Generation in the Wild—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