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 4376–4400 of 14297 papers

TitleStatusHype
ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate Statements?Code0
UniIR: Training and Benchmarking Universal Multimodal Information Retrievers—0
Outfit Completion via Conditional Set Transformation—0
A Two-Stage Adaptation of Large Language Models for Text RankingCode1
Bridging the Gap: A Unified Video Comprehension Framework for Moment Retrieval and Highlight DetectionCode1
Task Tree Retrieval For Robotic Cooking—0
SUT: a new multi-purpose synthetic dataset for Farsi document image analysisCode0
Novel Preprocessing Technique for Data Embedding in Engineering Code Generation Using Large Language Model—0
Boot and Switch: Alternating Distillation for Zero-Shot Dense RetrievalCode0
Safe-CLIP: Removing NSFW Concepts from Vision-and-Language ModelsCode1
SEINE: SEgment-based Indexing for NEural information retrieval—0
Noisy Self-Training with Synthetic Queries for Dense RetrievalCode0
Accelerating Hopfield Network Dynamics: Beyond Synchronous Updates and Forward EulerCode0
Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective—0
Releasing the CRaQAn (Coreference Resolution in Question-Answering): An open-source dataset and dataset creation methodology using instruction-following models—0
Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination—0
EVCap: Retrieval-Augmented Image Captioning with External Visual-Name Memory for Open-World Comprehension—0
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift—0
The Local Landscape of Phase Retrieval Under Limited Samples—0
HyperKon: A Self-Supervised Contrastive Network for Hyperspectral Image Analysis—0
See and Think: Embodied Agent in Virtual Environment—0
Relevance feedback strategies for recall-oriented neural information retrieval—0
Automatic Synthetic Data and Fine-grained Adaptive Feature Alignment for Composed Person RetrievalCode1
Coordinate-based Neural Network for Fourier Phase Retrieval—0
Custom Data Augmentation for low resource ASR using Bark and Retrieval-Based Voice Conversion—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