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 6576–6600 of 14297 papers

TitleStatusHype
End-to-End Multimodal Representation Learning for Video Dialog—0
Broken Neural Scaling LawsCode1
Deploying a Retrieval based Response Model for Task Oriented Dialogues—0
Phase Retrieval of Quaternion Signal via Wirtinger Flow—0
RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question AnsweringCode1
SciFact-Open: Towards open-domain scientific claim verificationCode1
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
DialogConv: A Lightweight Fully Convolutional Network for Multi-view Response Selection—0
Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence—0
XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic ParsingCode0
Lafite2: Few-shot Text-to-Image Generation—0
NAS-PRNet: Neural Architecture Search generated Phase Retrieval Net for Off-axis Quantitative Phase Imaging—0
Bridging the Training-Inference Gap for Dense Phrase Retrieval—0
A Regularized Conditional GAN for Posterior Sampling in Image Recovery ProblemsCode0
Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision—0
Context-Situated Pun GenerationCode0
Characterizing Verbatim Short-Term Memory in Neural Language ModelsCode0
Reliability-Aware Prediction via Uncertainty Learning for Person Image RetrievalCode1
Modeling Information Change in Science Communication with Semantically Matched Paraphrases—0
Subspace Representations for Soft Set Operations and Sentence SimilaritiesCode1
Online Information Retrieval Evaluation using the STELLA Framework—0
Gallery Filter Network for Person SearchCode1
TIARA: Multi-grained Retrieval for Robust Question Answering over Large Knowledge BasesCode0
ADMM based Fourier phase retrieval with untrained generative prior—0
Neural Eigenfunctions Are Structured Representation LearnersCode1
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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