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 6501–6550 of 14297 papers

TitleStatusHype
Improving Zero-shot LLM Re-Ranker with Risk Minimization—0
IM-RAG: Multi-Round Retrieval-Augmented Generation Through Learning Inner Monologues—0
Cross-modal Place Recognition in Image Databases using Event-based Sensors—0
Auto-JacoBin: Auto-encoder Jacobian Binary Hashing—0
An Accuracy-Enhanced Stemming Algorithm for Arabic Information Retrieval—0
Improving Biomedical Analogical Retrieval with Embedding of Structural Dependencies—0
Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies—0
Incomplete In-context Learning—0
In-context denoising with one-layer transformers: connections between attention and associative memory retrieval—0
Improving Bilingual Terminology Extraction from Comparable Corpora via Multiple Word-Space Models—0
Improving BERT-based Query-by-Document Retrieval with Multi-Task Optimization—0
In-Context Learning for Text Classification with Many Labels—0
Cross-Modal Manifold Learning for Cross-modal Retrieval—0
In-Context Learning with Long-Context Models: An In-Depth Exploration—0
Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation—0
In-Context Prompt Editing For Conditional Audio Generation—0
Improving average ranking precision in user searches for biomedical research datasets—0
Exploring Train and Test-Time Augmentations for Audio-Language Learning—0
Improving Attributed Text Generation of Large Language Models via Preference Learning—0
Cross-Modal Learning via Pairwise Constraints—0
Incorporating Intra-Class Variance to Fine-Grained Visual Recognition—0
AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System—0
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue—0
Incorporating Multimodal Information in Open-Domain Web Keyphrase Extraction—0
Incorporating Precedents for Legal Judgement Prediction on European Court of Human Rights Cases—0
Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks—0
Adaptive Substring Extraction and Modified Local NBNN Scoring for Binary Feature-based Local Mobile Visual Search without False Positives—0
Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation—0
Incorporating Semantic Textual Similarity and Lexical Matching for Information Retrieval—0
Increasing Papers' Discoverability with Precise Semantic Labeling: the sci.AI Platform—0
Incremental Attractor Neural Network Modelling of the Lifespan Retrieval Curve—0
Improving Acquisition Speed of X-Ray Ptychography through Spatial Undersampling and Regularization—0
Improving accuracy of GPT-3/4 results on biomedical data using a retrieval-augmented language model—0
Improving Accountability in Recommender Systems Research Through Reproducibility—0
Cross-Modality Personalization for Retrieval—0
Incremental Object Discovery in Time-Varying Image Collections—0
Improving Access to Trade and Investment Information in Thailand through Intelligent Document Retrieval—0
In defense of dual-encoders for neural ranking—0
In Defense of MinHash Over SimHash—0
End-to-End Supervised Product Quantization for Image Search and Retrieval—0
In Defense of RAG in the Era of Long-Context Language Models—0
Indexing of CNN Features for Large Scale Image Search—0
Improve Supervised Representation Learning with Masked Image Modeling—0
Improve Retrieval-based Dialogue System via Syntax-Informed Attention—0
Improved Visual Localization via Graph Smoothing—0
Cross-Modality Binary Code Learning via Fusion Similarity Hashing—0
Autoencoding the Retrieval Relevance of Medical Images—0
Indoor Information Retrieval using Lifelog Data—0
Improved Topic modeling in Twitter through Community Pooling—0
Improved Text-Image Matching by Mitigating Visual Semantic Hubs—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