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 6451–6475 of 14297 papers

TitleStatusHype
PolQA: Polish Question Answering Dataset—0
Improving RAG Retrieval via Propositional Content Extraction: a Speech Act Theory Approach—0
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching—0
Improving Raw Image Storage Efficiency by Exploiting Similarity—0
Cross-Modal Retrieval Augmentation for Multi-Modal Classification—0
Automated Answer Validation using Text Similarity—0
Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation—0
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization—0
Improving Content Retrievability in Search with Controllable Query Generation—0
Improving Retrieval-Augmented Neural Machine Translation with Monolingual Data—0
Cross-Modal Retrieval and Synthesis (X-MRS): Closing the Modality Gap in Shared Representation Learning—0
Auto-labelling of Bug Report using Natural Language Processing—0
An Acoustic Segment Model Based Segment Unit Selection Approach to Acoustic Scene Classification with Partial Utterances—0
Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources—0
Improving Retrieval in Sponsored Search by Leveraging Query Context Signals—0
Improving Clinical Question Answering with Multi-Task Learning: A Joint Approach for Answer Extraction and Medical Categorization—0
A New Fine-grained Alignment Method for Image-text Matching—0
Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking—0
Cross-Modal Pre-Aligned Method with Global and Local Information for Remote-Sensing Image and Text Retrieval—0
Improving Calibration in Deep Metric Learning With Cross-Example Softmax—0
Improving Biomedical Information Retrieval with Neural Retrievers—0
Cross-modal Place Recognition in Image Databases using Event-based Sensors—0
Improving Sparse Associative Memories by Escaping from Bogus Fixed Points—0
Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning—0
Auto-JacoBin: Auto-encoder Jacobian Binary Hashing—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