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 5226–5250 of 14297 papers

TitleStatusHype
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval ModelsCode0
Fine-grained Apparel Classification and Retrieval without rich annotationsCode0
Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise LevelsCode0
Combining Static and Contextualised Multilingual EmbeddingsCode0
From Play to Replay: Composed Video Retrieval for Temporally Fine-Grained VideosCode0
KnowZRel: Common Sense Knowledge-based Zero-Shot Relationship Retrieval for Generalised Scene Graph GenerationCode0
Bridging Search and Recommendation in Generative Retrieval: Does One Task Help the Other?—0
Do We Really Need Scene-specific Pose Encoders?—0
Do We Need to Differentiate Negative Candidates Before Training a Neural Ranker?—0
Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation—0
A Novel Line Integral Transform for 2D Affine-Invariant Shape Retrieval—0
Bridging Queries and Tables through Entities in Table Retrieval—0
Do ``Undocumented Workers'' == ``Illegal Aliens''? Differentiating Denotation and Connotation in Vector Spaces—0
Doubly-stochastic mining for heterogeneous retrieval—0
Bridging Modalities: Improving Universal Multimodal Retrieval by Multimodal Large Language Models—0
A Novel Incremental Cross-Modal Hashing Approach—0
Adversarial Retriever-Ranker for dense text retrieval—0
Double Retrieval and Ranking for Accurate Question Answering—0
Bridging Law and Data: Augmenting Reasoning via a Semi-Structured Dataset with IRAC methodology—0
A novel image tag completion method based on convolutional neural network—0
Do Retrieval-Augmented Language Models Adapt to Varying User Needs?—0
Do RAG Systems Suffer From Positional Bias?—0
A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval—0
Adversarial Prediction Games for Multivariate Losses—0
A Comparative Study on TF-IDF feature Weighting Method and its Analysis using Unstructured Dataset—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