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 7476–7500 of 14297 papers

TitleStatusHype
Semi-Parametric Neural Image SynthesisCode6
Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking—0
Exoplanet Cartography using Convolutional Neural Networks—0
Signal Recovery with Non-Expansive Generative Network Priors—0
Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging—0
Faster Learned Sparse Retrieval with Guided TraversalCode0
Entity-Conditioned Question Generation for Robust Attention Distribution in Neural Information RetrievalCode0
Progressive Learning for Image Retrieval with Hybrid-Modality Queries—0
RelViT: Concept-guided Vision Transformer for Visual Relational ReasoningCode1
Food Recommendations for Reducing Water FootprintCode0
On Leveraging Variational Graph Embeddings for Open World Compositional Zero-Shot Learning—0
Dual Skipping Guidance for Document Retrieval with Learned Sparse RepresentationsCode0
GRM: Gradient Rectification Module for Visual Place Retrieval—0
Training and challenging models for text-guided fashion image retrievalCode1
Zero-shot Query Contextualization for Conversational SearchCode0
Sparse and Dense Approaches for the Full-rank Retrieval of Responses for DialoguesCode1
Pre-train a Discriminative Text Encoder for Dense Retrieval via Contrastive Span PredictionCode1
Balancing Fairness and Accuracy in Sentiment Detection using Multiple Black Box ModelsCode0
Autoregressive Search Engines: Generating Substrings as Document IdentifiersCode2
A Multi-level Alignment Training Scheme for Video-and-Language Grounding—0
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion—0
Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few UtterancesCode1
A Summary of the ALQAC 2021 Competition—0
Leveraging Deepfakes to Close the Domain Gap between Real and Synthetic Images in Facial Capture Pipelines—0
Convex Augmentation for Total Variation Based Phase Retrieval—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