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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 1901–1925 of 14297 papers

TitleStatusHype
Bi-directional Training for Composed Image Retrieval via Text Prompt LearningCode1
Hierarchical Attention Fusion for Geo-LocalizationCode1
ChiTransformer:Towards Reliable Stereo from CuesCode1
Feature Re-Learning with Data Augmentation for Video Relevance PredictionCode1
FedCMR: Federated Cross-Modal RetrievalCode1
Federated Recommendation via Hybrid Retrieval Augmented GenerationCode1
FELM: Benchmarking Factuality Evaluation of Large Language ModelsCode1
Probabilistic Embeddings RevisitedCode1
FETA: Towards Specializing Foundation Models for Expert Task ApplicationsCode1
FeTaQA: Free-form Table Question AnsweringCode1
Few-Shot Conversational Dense RetrievalCode1
Few-Shot Generative Conversational Query RewritingCode1
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal UnderstandingCode1
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich NetworksCode1
FILIP: Fine-grained Interactive Language-Image Pre-TrainingCode1
Hierarchical Contrast for Unsupervised Skeleton-based Action Representation LearningCode1
Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based ChatbotsCode1
Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn DialogueCode1
HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World ClaimsCode1
CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-CheckingCode1
Chitransformer: Towards Reliable Stereo From CuesCode1
Prompting Visual-Language Models for Efficient Video UnderstandingCode1
HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-trainingCode1
FineCIR: Explicit Parsing of Fine-Grained Modification Semantics for Composed Image RetrievalCode1
Hierarchical Document Refinement for Long-context Retrieval-augmented GenerationCode1
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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