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 5175 of 14297 papers

TitleStatusHype
Retrieval-Augmented Generation for AI-Generated Content: A SurveyCode5
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue AbilitiesCode5
RAPTOR: Recursive Abstractive Processing for Tree-Organized RetrievalCode5
Chatlaw: A Multi-Agent Collaborative Legal Assistant with Knowledge Graph Enhanced Mixture-of-Experts Large Language ModelCode5
ImageBind: One Embedding Space To Bind Them AllCode5
Chinese CLIP: Contrastive Vision-Language Pretraining in ChineseCode5
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationCode5
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning AgentsCode4
DeepResearch Bench: A Comprehensive Benchmark for Deep Research AgentsCode4
A Survey of LLM DATACode4
R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement LearningCode4
SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory SynthesisCode4
s3: You Don't Need That Much Data to Train a Search Agent via RLCode4
OnPrem.LLM: A Privacy-Conscious Document Intelligence ToolkitCode4
FG-CLIP: Fine-Grained Visual and Textual AlignmentCode4
Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and ModalityCode4
Retrieval-Augmented Generation with Hierarchical KnowledgeCode4
VLog: Video-Language Models by Generative Retrieval of Narration VocabularyCode4
Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language ModelsCode4
DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement LearningCode4
ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning AgentsCode4
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented GenerationCode4
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process RewardingCode4
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental LearningCode4
Gated Delta Networks: Improving Mamba2 with Delta RuleCode4
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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