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 5526–5550 of 14297 papers

TitleStatusHype
ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense RetrievalCode1
Advancing Full-Text Search Lemmatization Techniques with Paradigm Retrieval from OpenCorpora—0
BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrieval—0
The Web Can Be Your Oyster for Improving Large Language ModelsCode1
Tram: A Token-level Retrieval-augmented Mechanism for Source Code SummarizationCode0
TOME: A Two-stage Approach for Model-based Retrieval—0
Query Performance Prediction: From Ad-hoc to Conversational SearchCode1
ONE-PEACE: Exploring One General Representation Model Toward Unlimited ModalitiesCode3
Seq-HGNN: Learning Sequential Node Representation on Heterogeneous GraphCode1
Selective Query Processing: a Risk-Sensitive Selection of System Configurations—0
Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language ModelsCode1
Multi-Grained Knowledge Retrieval for End-to-End Task-Oriented DialogCode0
From Region to Patch: Attribute-Aware Foreground-Background Contrastive Learning for Fine-Grained Fashion RetrievalCode0
Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries—0
CLIP-GCD: Simple Language Guided Generalized Category Discovery—0
Object Re-Identification from Point Clouds—0
Large Language Models are Built-in Autoregressive Search EnginesCode1
Robust and lightweight audio fingerprint for Automatic Content Recognition—0
Phase Retrieval via Model-Free Power Flow Jacobian RecoveryCode0
Hybrid and Collaborative Passage RerankingCode0
Soft Prompt Decoding for Multilingual Dense Retrieval—0
KEPR: Knowledge Enhancement and Plausibility Ranking for Generative Commonsense Question AnsweringCode0
RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model OutputsCode1
M^6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode0
Efficient and Effective Tree-based and Neural Learning to Rank—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