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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 8026–8050 of 14297 papers

TitleStatusHype
CLICKER: A Computational LInguistics Classification Scheme for Educational ResourcesCode1
Evidentiality-guided Generation for Knowledge-Intensive NLP TasksCode1
Self-supervised Enhancement of Latent Discovery in GANs—0
Deep Hash Distillation for Image RetrievalCode1
Unsupervised Dense Information Retrieval with Contrastive LearningCode1
MAVE: A Product Dataset for Multi-source Attribute Value ExtractionCode1
CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language PairsCode1
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge TransferCode1
CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning—0
CODER: An efficient framework for improving retrieval through COntextual Document Embedding RerankingCode0
Selecting the suitable resampling strategy for imbalanced data classification regarding dataset properties—0
Large Dual Encoders Are Generalizable RetrieversCode1
Text Mining Through Label Induction Grouping Algorithm Based Method—0
Design Challenges for a Multi-Perspective Search EngineCode0
Learning Cross-Lingual IR from an English RetrieverCode1
KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense GenerationCode0
Modality-Aware Triplet Hard Mining for Zero-shot Sketch-Based Image RetrievalCode0
Value Retrieval with Arbitrary Queries for Form-like DocumentsCode1
Cognition-aware Cognate DetectionCode0
Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake VideosCode0
Boosted Dense Retriever—0
Learning to Retrieve Passages without SupervisionCode1
DeepDiffusion: Unsupervised Learning of Retrieval-adapted Representations via Diffusion-based Ranking on Latent Feature ManifoldCode0
Conversational Search with Mixed-Initiative -- Asking Good Clarification Questions backed-up by Passage Retrieval—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