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

Showing 91019150 of 14297 papers

TitleStatusHype
Efficient Discrete Supervised Hashing for Large-scale Cross-modal Retrieval0
``None of the Above'': Measure Uncertainty in Dialog Response Retrieval0
Non-Inherent Feature Compatible Learning0
Non-Iterative Phase Retrieval With Cascaded Neural Networks0
Non-linear Label Ranking for Large-scale Prediction of Long-Term User Interests0
Multi-Granularity and Multi-modal Feature Interaction Approach for Text Video Retrieval0
Enhancing Document Retrieval for Curating N-ary Relations in Knowledge Bases0
Non-Parametric Adaptation for Neural Machine Translation0
Nonparametric Bayesian Storyline Detection from Microtexts0
Affine-modeled video extraction from a single motion blurred image0
On the Evaluation of the Plausibility and Faithfulness of Sentiment Analysis Explanations0
Non-Parametric Temporal Adaptation for Social Media Topic Classification0
On the Exploration of Convolutional Fusion Networks for Visual Recognition0
Non-rigid 3D shape retrieval based on multi-view metric learning0
Nonstationary Distance Metric Learning0
Non-Stationary Power System Forced Oscillation Analysis using Synchrosqueezing Transform0
Multi-Grained Attention Network With Mutual Exclusion for Composed Query-Based Image Retrieval0
No Pattern, No Recognition: a Survey about Reproducibility and Distortion Issues of Text Clustering and Topic Modeling0
No Captions, No Problem: Captionless 3D-CLIP Alignment with Hard Negatives via CLIP Knowledge and LLMs0
On the Estimation of Image-matching Uncertainty in Visual Place Recognition0
Normalized Human Pose Features for Human Action Video Alignment0
Enhancing Fact Retrieval in PLMs through Truthfulness0
Learning Test-time Augmentation for Content-based Image Retrieval0
Multi-Frequency Phase Retrieval for Antenna Measurements0
MultiFinRAG: An Optimized Multimodal Retrieval-Augmented Generation (RAG) Framework for Financial Question Answering0
Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models0
On the Evaluation Metric for Hashing0
Evaluation of Field-Aware Neural Ranking Models for Recipe Search0
An alternative proof of the vulnerability of retrieval in high intrinsic dimensionality neighborhood0
NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding0
Not just a matter of semantics: the relationship between visual similarity and semantic similarity0
Enhancing Healthcare through Large Language Models: A Study on Medical Question Answering0
Multi-Field Adaptive Retrieval0
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification0
Efficient Decoding of Compositional Structure in Holistic Representations0
Multi-feature Fusion for Image Retrieval Using Constrained Dominant Sets0
Novelty and Coverage in context-based information filtering0
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning0
NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models0
NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing0
Npix2Cpix: A GAN-Based Image-to-Image Translation Network With Retrieval- Classification Integration for Watermark Retrieval From Historical Document Images0
A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions0
Multi-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval0
CancerKG.ORG A Web-scale, Interactive, Verifiable Knowledge Graph-LLM Hybrid for Assisting with Optimal Cancer Treatment and Care0
Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Models0
NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models0
NV-Retriever: Improving text embedding models with effective hard-negative mining0
NYCU ML Lab LLAMA: Prefix tuning using LLAMA for Informationa Retrieval0
O1 Embedder: Let Retrievers Think Before Action0
A picture is worth a thousand words: Using OpenClipArt library for enriching IndoWordNet0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second183.53Unverified
2ElasticsearchQueries per second21.8Unverified
3BM25-PTQueries per second6.49Unverified
4Rank-BM25Queries per second1.18Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second20.88Unverified
2ElasticsearchQueries per second7.11Unverified
3Rank-BM25Queries per second0.04Unverified
#ModelMetricClaimedVerifiedStatus
1BM25SQueries per second41.85Unverified
2ElasticsearchQueries per second12.16Unverified
3Rank-BM25Queries per second0.1Unverified
#ModelMetricClaimedVerifiedStatus
1FLMRRecall@589.32Unverified
2RA-VQARecall@582.84Unverified
#ModelMetricClaimedVerifiedStatus
1PreFLMRRecall@562.1Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-KIStext-to-video Mean Rank30Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP4OutfitRecall@57.59Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAGAccuracy (Top-1)82.1Unverified
#ModelMetricClaimedVerifiedStatus
1COLTCOMP@84.55Unverified
#ModelMetricClaimedVerifiedStatus
1hello0L1,121,222Unverified