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 6451–6475 of 14297 papers

TitleStatusHype
Open-Domain Conversational Question Answering with Historical AnswersCode0
Thermodynamics of bidirectional associative memories—0
Data-Efficient Autoregressive Document Retrieval for Fact Verification—0
Cross-Modal Adapter for Text-Video RetrievalCode1
ArcAid: Analysis of Archaeological Artifacts using DrawingsCode0
CapEnrich: Enriching Caption Semantics for Web Images via Cross-modal Pre-trained KnowledgeCode0
Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications—0
Task-aware Retrieval with InstructionsCode1
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language ModelsCode2
Structural Segmentation and Labeling of Tabla Solo Performances—0
MM-Locate-News: Multimodal Focus Location Estimation in NewsCode0
Navigating Connected Memories with a Task-oriented Dialog SystemCode1
PromptCap: Prompt-Guided Task-Aware Image CaptioningCode1
Adaptation Approaches for Nearest Neighbor Language Models—0
Error-Robust Retrieval for Chinese Spelling CheckCode0
Music Instrument Classification ReprogrammedCode0
Show Me the Instruments: Musical Instrument Retrieval from Mixture AudioCode1
DINER: Disorder-Invariant Implicit Neural Representation—0
Large Language Models Struggle to Learn Long-Tail KnowledgeCode1
Visually Grounded VQA by Lattice-based RetrievalCode0
Evidence-based Match-status-Aware Gait Recognition for Out-of-Gallery Gait Identification—0
Extracting task trees using knowledge retrieval search algorithms in functional object-oriented network—0
Technological taxonomies for hypernym and hyponym retrieval in patent textsCode0
Is my automatic audio captioning system so bad? spider-max: a metric to consider several caption candidatesCode1
Describing emotions with acoustic property prompts for speech emotion recognition—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