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 36763700 of 14297 papers

TitleStatusHype
Multi-Turn Multi-Modal Question Clarification for Enhanced Conversational Understanding0
Revisiting Robust RAG: Do We Still Need Complex Robust Training in the Era of Powerful LLMs?0
If Attention Serves as a Cognitive Model of Human Memory Retrieval, What is the Plausible Memory Representation?0
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization0
Investigating Language Preference of Multilingual RAG Systems0
Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs0
Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation0
QuOTE: Question-Oriented Text Embeddings0
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVMCode0
SpeechT-RAG: Reliable Depression Detection in LLMs with Retrieval-Augmented Generation Using Speech Timing Information0
TPCap: Unlocking Zero-Shot Image Captioning with Trigger-Augmented and Multi-Modal Purification Modules0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation0
An Open-Source Web-Based Tool for Evaluating Open-Source Large Language Models Leveraging Information Retrieval from Custom Documents0
NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question AnsweringCode0
Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs0
Retrieval-augmented Encoders for Extreme Multi-label Text Classification0
LSTM-based Selective Dense Text Retrieval Guided by Sparse Lexical Retrieval0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations0
Optimal lower Lipschitz bounds for ReLU layers, saturation, and phase retrieval0
Agentic Verification for Ambiguous Query Disambiguation0
ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation0
Improving TCM Question Answering through Tree-Organized Self-Reflective Retrieval with LLMs0
Semantic Ads Retrieval at Walmart eCommerce with Language Models Progressively Trained on Multiple Knowledge Domains0
KIMAs: A Configurable Knowledge Integrated Multi-Agent System0
ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation0
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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