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 14201–14250 of 14297 papers

TitleStatusHype
Retrieval Augmented Generation for Domain-specific Question Answering—0
Retrieval-Augmented Generation for Domain-Specific Question Answering: A Case Study on Pittsburgh and CMU—0
Retrieval Augmented Generation for Dynamic Graph Modeling—0
Retrieval-Augmented Generation for Generative Artificial Intelligence in Medicine—0
Query Expansion for Survey Question Retrieval in the Social Sciences—0
Query Expansion and Entity Weighting for Query Reformulation Retrieval in Voice Assistant Systems—0
Retrieval-Augmented Generation for Mobile Edge Computing via Large Language Model—0
Retrieval-Augmented Generation for Natural Language Processing: A Survey—0
Retrieval-Augmented Generation for Service Discovery: Chunking Strategies and Benchmarking—0
Retrieval Augmented Generation for Topic Modeling in Organizational Research: An Introduction with Empirical Demonstration—0
Query-driven Relevant Paragraph Extraction from Legal Judgments—0
Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications—0
Retrieval Augmented Generation Integrated Large Language Models in Smart Contract Vulnerability Detection—0
Dense Passage Retrieval: Is it Retrieving?—0
Retrieval-Augmented Generation of Ontologies from Relational Databases—0
Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach—0
Open Domain Question Answering over Tables via Dense Retrieval—0
Query-driven Document-level Scientific Evidence Extraction from Biomedical Studies—0
Retrieval-Augmented Generation with Estimation of Source Reliability—0
Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning—0
Query by String word spotting based on character bi-gram indexing—0
Query by Semantic Sketch—0
X-Ray Image Compression Using Convolutional Recurrent Neural Networks—0
Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering—0
Query-by-Example Image Retrieval using Visual Dependency Representations—0
Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain—0
QueryBuilder: Human-in-the-Loop Query Development for Information Retrieval—0
Retrieval Augmented Image Harmonization—0
Retrieval-augmented in-context learning for multimodal large language models in disease classification—0
Query Adaptive Similarity for Large Scale Object Retrieval—0
Retrieval-Augmented Instruction Tuning for Automated Process Engineering Calculations : A Tool-Chaining Problem-Solving Framework with Attributable Reflection—0
Variations in Relevance Judgments and the Shelf Life of Test Collections—0
Retrieval Augmented Language Model Pre-Training—0
Query Adaptive Late Fusion for Image Retrieval—0
Query-adaptive Image Retrieval by Deep Weighted Hashing—0
Retrieval-Augmented Meta Learning for Low-Resource Text Classification—0
Retrieval-Augmented Mining of Temporal Logic Specifications from Data—0
Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning—0
Retrieval-augmented Multi-label Text Classification—0
Query2doc: Query Expansion with Large Language Models—0
Quels corpus d'entraînement pour l'expansion de requêtes par plongement de mots : application à la recherche de microblogs culturels—0
Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models—0
Retrieval-Augmented Multimodal Language Modeling—0
Retrieval-Augmented Natural Language Reasoning for Explainable Visual Question Answering—0
Open-book Video Captioning with Retrieve-Copy-Generate Network—0
Retrieval-Augmented Neural Response Generation Using Logical Reasoning and Relevance Scoring—0
Que2Engage: Embedding-based Retrieval for Relevant and Engaging Products at Facebook Marketplace—0
QUB-Cirdan at "Discharge Me!": Zero shot discharge letter generation by open-source LLM—0
Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning—0
Retrieval-Augmented Purifier for Robust LLM-Empowered Recommendation—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