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 9226–9250 of 14297 papers

TitleStatusHype
BUTTER: A Representation Learning Framework for Bi-directional Music-Sentence Retrieval and Generation—0
ByteCover3: Accurate Cover Song Identification on Short Queries—0
C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval—0
C^3DRec: Cloud-Client Cooperative Deep Learning for Temporal Recommendation in the Post-GDPR Era—0
C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation—0
Cache-Aided Multi-User Private Information Retrieval using PDAs—0
Cache-Augmented Latent Topic Language Models for Speech Retrieval—0
Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation—0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation—0
Caching and Reproducibility: Making Data Science experiments faster and FAIRer—0
Caching Historical Embeddings in Conversational Search—0
CAD-NeRF: Learning NeRFs from Uncalibrated Few-view Images by CAD Model Retrieval—0
CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability—0
CAIBC: Capturing All-round Information Beyond Color for Text-based Person Retrieval—0
CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents—0
CAISSON: Concept-Augmented Inference Suite of Self-Organizing Neural Networks—0
Calibrated Decision-Making through LLM-Assisted Retrieval—0
Calibrated neighborhood aware confidence measure for deep metric learning—0
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification—0
Calibrating Probabilistic Embeddings for Cross-Modal Retrieval—0
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning—0
Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning—0
Calibration of Machine Reading Systems at Scale—0
Calibration of Machine Reading Systems at Scale—0
CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition—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