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 1101–1150 of 14297 papers

TitleStatusHype
Revisiting Robust RAG: Do We Still Need Complex Robust Training in the Era of Powerful LLMs?—0
CLASS: Enhancing Cross-Modal Text-Molecule Retrieval Performance and Training Efficiency—0
Cognitive-Aligned Document Selection for Retrieval-augmented Generation—0
If Attention Serves as a Cognitive Model of Human Memory Retrieval, What is the Plausible Memory Representation?—0
Does RAG Really Perform Bad For Long-Context Processing?—0
Descriminative-Generative Custom Tokens for Vision-Language Models—0
ILIAS: Instance-Level Image retrieval At ScaleCode1
FineFilter: A Fine-grained Noise Filtering Mechanism for Retrieval-Augmented Large Language Models—0
Reinforced Information Retrieval—0
Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information RetrievalCode3
Multi-Turn Multi-Modal Question Clarification for Enhanced Conversational Understanding—0
Fast or Better? Balancing Accuracy and Cost in Retrieval-Augmented Generation with Flexible User ControlCode0
Multi-Modal Retrieval Augmentation for Open-Ended and Knowledge-Intensive Video Question Answering—0
FairDiverse: A Comprehensive Toolkit for Fair and Diverse Information Retrieval AlgorithmsCode1
GPU-accelerated Multi-relational Parallel Graph Retrieval for Web-scale Recommendations—0
FaMTEB: Massive Text Embedding Benchmark in Persian Language—0
Improving Similar Case Retrieval Ranking Performance By Revisiting RankSVMCode0
TPCap: Unlocking Zero-Shot Image Captioning with Trigger-Augmented and Multi-Modal Purification Modules—0
Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs—0
RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM GenerationCode2
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization—0
Investigating Language Preference of Multilingual RAG Systems—0
Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language ModelsCode1
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation—0
NavRAG: Generating User Demand Instructions for Embodied Navigation through Retrieval-Augmented LLMCode2
Knowledge Graph-Driven Retrieval-Augmented Generation: Integrating Deepseek-R1 with Weaviate for Advanced Chatbot ApplicationsCode1
SpeechT-RAG: Reliable Depression Detection in LLMs with Retrieval-Augmented Generation Using Speech Timing Information—0
Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation—0
QuOTE: Question-Oriented Text Embeddings—0
LSTM-based Selective Dense Text Retrieval Guided by Sparse Lexical Retrieval—0
Retrieval-augmented Encoders for Extreme Multi-label Text Classification—0
NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question AnsweringCode0
An Open-Source Web-Based Tool for Evaluating Open-Source Large Language Models Leveraging Information Retrieval from Custom Documents—0
Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs—0
ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation—0
Agentic Verification for Ambiguous Query Disambiguation—0
Optimal lower Lipschitz bounds for ReLU layers, saturation, and phase retrieval—0
Post-training an LLM for RAG? Train on Self-Generated Demonstrations—0
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAGCode2
Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights—0
Improving TCM Question Answering through Tree-Organized Self-Reflective Retrieval with LLMs—0
Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMsCode1
Semantic Ads Retrieval at Walmart eCommerce with Language Models Progressively Trained on Multiple Knowledge Domains—0
KIMAs: A Configurable Knowledge Integrated Multi-Agent System—0
ImageRAG: Dynamic Image Retrieval for Reference-Guided Image Generation—0
ParetoRAG: Leveraging Sentence-Context Attention for Robust and Efficient Retrieval-Augmented Generation—0
Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAGCode0
Explanation based In-Context Demonstrations Retrieval for Multilingual Grammatical Error CorrectionCode0
Examining Multilingual Embedding Models Cross-Lingually Through LLM-Generated Adversarial Examples—0
Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented GenerationCode3
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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