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 8251–8275 of 14297 papers

TitleStatusHype
Practical and Light-weight Secure Aggregation for Federated Submodel Learning—0
Multi-input Architecture and Disentangled Representation Learning for Multi-dimensional Modeling of Music Similarity—0
Assessing Effectiveness of Using Internal Signals for Check-Worthy Claim Identification in Unlabeled Data for Automated Fact-Checking—0
Classification of Goods Using Text Descriptions With Sentences Retrieval—0
LISN @ WMT 2021—0
Incorporating Semantic Textual Similarity and Lexical Matching for Information Retrieval—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
Decoding Word Embeddings with Brain-Based Semantic Features—0
An in-depth look at Euclidean disk embeddings for structure preserving parsing—0
Detection of Puffery on the English WikipediaCode0
Personalized Search-based Query Rewrite System for Conversational AI—0
The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task—0
Cross-Lingual Training of Dense Retrievers for Document Retrieval—0
Verdict Inference with Claim and Retrieved Elements Using RoBERTa—0
Neural Re-rankers for Evidence Retrieval in the FEVEROUS Task—0
Combining sentence and table evidence to predict veracity of factual claims using TaPaS and RoBERTa—0
FaBULOUS: Fact-checking Based on Understanding of Language Over Unstructured and Structured information—0
Modeling Entity Knowledge for Fact Verification—0
Evidence Selection as a Token-Level Prediction TaskCode1
Matching-oriented Embedding Quantization For Ad-hoc RetrievalCode1
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence AnnotationCode1
Inflate and Shrink:Enriching and Reducing Interactions for Fast Text-Image Retrieval—0
Code-switched inspired losses for spoken dialog representations—0
Exploring Methods for Generating Feedback Comments for Writing LearningCode0
Leveraging Capsule Routing to Associate Knowledge with Medical Literature HierarchicallyCode0
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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