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 9401–9425 of 14297 papers

TitleStatusHype
No-Regret Caching via Online Mirror Descent—0
Subgraph nomination: Query by Example Subgraph Retrieval in Networks—0
A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor SearchCode1
Deep Triplet Hashing Network for Case-based Medical Image RetrievalCode1
A Graph-based Relevance Matching Model for Ad-hoc RetrievalCode0
DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents—0
BERTaú: Itaú BERT for digital customer service—0
Perceptions of Diversity in Electronic Music: the Impact of Listener, Artist, and Track CharacteristicsCode0
Deep Learning for Instance Retrieval: A Survey—0
Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations—0
Novel Recording Studio Features for Music Information Retrieval—0
Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularization—0
A Two-stage Framework for Compound Figure Separation—0
Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task—0
A Review of Speaker Diarization: Recent Advances with Deep Learning—0
Medical Information Retrieval and Interpretation: A Question-Answer based Interaction Model—0
Advances and Challenges in Conversational Recommender Systems: A Survey—0
Impact of Response Latency on User Behaviour in Mobile Web Search—0
It Takes Two to Tango: Combining Visual and Textual Information for Detecting Duplicate Video-Based Bug ReportsCode0
Geometric Moment Invariants to Motion Blur—0
Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning MethodCode1
Assessing the Benefits of Model Ensembles in Neural Re-Ranking for Passage Retrieval—0
Item Recommendation from Implicit Feedback—0
Content Selection Network for Document-grounded Retrieval-based ChatbotsCode0
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual RetrievalCode0
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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