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 9126–9150 of 14297 papers

TitleStatusHype
Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models—0
On the Evaluation Metric for Hashing—0
Evaluation of Field-Aware Neural Ranking Models for Recipe Search—0
An alternative proof of the vulnerability of retrieval in high intrinsic dimensionality neighborhood—0
NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding—0
Not just a matter of semantics: the relationship between visual similarity and semantic similarity—0
Enhancing Healthcare through Large Language Models: A Study on Medical Question Answering—0
Multi-Field Adaptive Retrieval—0
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification—0
Efficient Decoding of Compositional Structure in Holistic Representations—0
Multi-feature Fusion for Image Retrieval Using Constrained Dominant Sets—0
Novelty and Coverage in context-based information filtering—0
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning—0
NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models—0
NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing—0
Npix2Cpix: A GAN-Based Image-to-Image Translation Network With Retrieval- Classification Integration for Watermark Retrieval From Historical Document Images—0
A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions—0
Multi-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval—0
CancerKG.ORG A Web-scale, Interactive, Verifiable Knowledge Graph-LLM Hybrid for Assisting with Optimal Cancer Treatment and Care—0
Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Models—0
NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models—0
NV-Retriever: Improving text embedding models with effective hard-negative mining—0
NYCU ML Lab LLAMA: Prefix tuning using LLAMA for Informationa Retrieval—0
O1 Embedder: Let Retrievers Think Before Action—0
A picture is worth a thousand words: Using OpenClipArt library for enriching IndoWordNet—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