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 2851–2875 of 14297 papers

TitleStatusHype
Deep Fragment Embeddings for Bidirectional Image Sentence Mapping—0
Deep Fusion of Multi-attentive Local and Global Features with Higher Efficiency for Image Retrieval—0
Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check—0
Boosted Dense Retriever—0
Annotation of Computer Science Papers for Semantic Relation Extrac-tion—0
Boosted Dense Retriever—0
BoolQuestions: Does Dense Retrieval Understand Boolean Logic in Language?—0
Annotation-free Learning of Deep Representations for Word Spotting using Synthetic Data and Self Labeling—0
Adversarial Attack on Deep Product Quantization Network for Image Retrieval—0
Boolean-aware Attention for Dense Retrieval—0
Annotation Cost-Efficient Active Learning for Deep Metric Learning Driven Remote Sensing Image Retrieval—0
Book Review: Graph-Based Natural Language Processing and Information Retrieval by Rada Mihalcea and Dragomir Radev—0
BookQA: Stories of Challenges and Opportunities—0
Annotation Cost Efficient Active Learning for Content Based Image Retrieval—0
Adversarial Attack on Deep Cross-Modal Hamming Retrieval—0
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model Inversion—0
Deep Hashing with Hash Center Update for Efficient Image Retrieval—0
Deep Image Retrieval is not Robust to Label Noise—0
Book QA: Stories of Challenges and Opportunities—0
Advancing Vietnamese Information Retrieval with Learning Objective and Benchmark—0
An NMF Perspective on Binary Hashing—0
A Comparative Analysis of Faithfulness Metrics and Humans in Citation Evaluation—0
An Issue-oriented Syllabus Retrieval System using Terminology-based Syllabus Structuring and Visualization—0
BM25 Query Augmentation Learned End-to-End—0
ANISE: Assembly-based Neural Implicit Surface rEconstruction—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