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 11701–11750 of 14297 papers

TitleStatusHype
Implementation Notes for the Soft Cosine Measure—0
Implementation of an efficient Fuzzy Logic based Information Retrieval System—0
Implementation of a noisy hyperlink removal system: A semantic and relatedness approach—0
Implementing Learning Principles with a Personal AI Tutor: A Case Study—0
Implicit Negative Feedback in Clinical Information Retrieval—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution—0
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion—0
Implicit semantic-based personalized micro-videos recommendation—0
Important Attribute Identification in Knowledge Graph—0
Improv Chat: Second Response Generation for Chatbot—0
Improved Answer Selection with Pre-Trained Word Embeddings—0
Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval—0
Improved Deep Metric Learning with Multi-class N-pair Loss Objective—0
Improve Dense Passage Retrieval with Entailment Tuning—0
Improved Hamming Distance Search Using Variable Length Substrings—0
Improved Radar Localization on Lidar Maps Using Shared Embedding—0
Improved Search in Hamming Space using Deep Multi-Index Hashing—0
Improved Text-Image Matching by Mitigating Visual Semantic Hubs—0
Improved Topic modeling in Twitter through Community Pooling—0
Improved Visual Localization via Graph Smoothing—0
Improve Retrieval-based Dialogue System via Syntax-Informed Attention—0
Improve Supervised Representation Learning with Masked Image Modeling—0
Improving Access to Trade and Investment Information in Thailand through Intelligent Document Retrieval—0
Improving Accountability in Recommender Systems Research Through Reproducibility—0
Improving accuracy of GPT-3/4 results on biomedical data using a retrieval-augmented language model—0
Improving Acquisition Speed of X-Ray Ptychography through Spatial Undersampling and Regularization—0
Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation—0
Improving Attributed Text Generation of Large Language Models via Preference Learning—0
Exploring Train and Test-Time Augmentations for Audio-Language Learning—0
Improving average ranking precision in user searches for biomedical research datasets—0
Improving BERT-based Query-by-Document Retrieval with Multi-Task Optimization—0
Improving Bilingual Terminology Extraction from Comparable Corpora via Multiple Word-Space Models—0
Improving Biomedical Analogical Retrieval with Embedding of Structural Dependencies—0
Improving Biomedical Information Retrieval with Neural Retrievers—0
Improving Calibration in Deep Metric Learning With Cross-Example Softmax—0
Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking—0
Improving Clinical Question Answering with Multi-Task Learning: A Joint Approach for Answer Extraction and Medical Categorization—0
Improving Commonsense Question Answering by Graph-based Iterative Retrieval over Multiple Knowledge Sources—0
Improving Content Retrievability in Search with Controllable Query Generation—0
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization—0
Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation—0
Improving Cross-lingual Representation for Semantic Retrieval with Code-switching—0
Improving Deep Binary Embedding Networks by Order-aware Reweighting of Triplets—0
Improving Document Ranking using Query Expansion and Classification Techniques for Mixed Script Information Retrieval—0
Improving Document Representations by Generating Pseudo Query Embeddings for Dense Retrieval—0
Improving Domain-Specific Retrieval by NLI Fine-Tuning—0
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining—0
Improving Embedding Accuracy for Document Retrieval Using Entity Relationship Maps and Model-Aware Contrastive Sampling—0
Improving Embedding-based Large-scale Retrieval via Label Enhancement—0
Improving embedding with contrastive fine-tuning on small datasets with expert-augmented scores—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