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 9776–9800 of 14297 papers

TitleStatusHype
Flexible retrieval with NMSLIB and FlexNeuARTCode1
Cycle-Contrast for Self-Supervised Video Representation Learning—0
RSPNet: Relative Speed Perception for Unsupervised Video Representation LearningCode1
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples—0
Effective FAQ Retrieval and Question Matching With Unsupervised Knowledge Injection—0
A Clarifying Question Selection System from NTES_ALONG in Convai3 Challenge—0
Exploiting Neural Query Translation into Cross Lingual Information Retrieval—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Where to Look and How to Describe: Fashion Image Retrieval with an Attentional Heterogeneous Bilinear Network—0
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language InferenceCode1
COUGH: A Challenge Dataset and Models for COVID-19 FAQ RetrievalCode1
Deep Graph Matching and Searching for Semantic Code Retrieval—0
XDM: Improving Sequential Deep Matching with Unclicked User Behaviors for Recommender SystemCode0
Neural networks for inverse control with system priors—0
Unlocking Inverse Problems Using Deep Learning: Breaking Symmetries in Phase Retrieval—0
Deep Learning Initialized Phase Retrieval—0
Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-trainingCode1
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human PoseCode0
Answering Open-Domain Questions of Varying Reasoning Steps from TextCode1
Neural Passage Retrieval with Improved Negative Contrast—0
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity LearningCode0
Migratable AI: Personalizing Dialog Conversations with migration context—0
Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval—0
Should Graph Convolution Trust Neighbors? A Simple Causal Inference MethodCode1
Scientific Claim Verification with VERT5ERINI—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