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 51–100 of 14297 papers

TitleStatusHype
Agentic Retrieval-Augmented Generation: A Survey on Agentic RAGCode5
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and InferenceCode5
TrustRAG: An Information Assistant with Retrieval Augmented GenerationCode5
MiniRAG: Towards Extremely Simple Retrieval-Augmented GenerationCode5
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMsCode5
Make Your LLM Fully Utilize the ContextCode5
RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query ParallelismCode5
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain KnowledgeCode4
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attentionCode4
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionCode4
Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language ModelingCode4
s3: You Don't Need That Much Data to Train a Search Agent via RLCode4
LLM2CLIP: Powerful Language Model Unlocks Richer Visual RepresentationCode4
Chain-of-Discussion: A Multi-Model Framework for Complex Evidence-Based Question AnsweringCode4
RETSim: Resilient and Efficient Text SimilarityCode4
SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory SynthesisCode4
Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksCode4
Retrieval-Augmented Generation for Large Language Models: A SurveyCode4
Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up QuestionsCode4
Bryndza at ClimateActivism 2024: Stance, Target and Hate Event Detection via Retrieval-Augmented GPT-4 and LLaMACode4
Retrieval-Augmented Generation with Hierarchical KnowledgeCode4
Resources for Brewing BEIR: Reproducible Reference Models and an Official LeaderboardCode4
AlignScore: Evaluating Factual Consistency with a Unified Alignment FunctionCode4
Long-CLIP: Unlocking the Long-Text Capability of CLIPCode4
Retrieval-Generation Synergy Augmented Large Language ModelsCode4
SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted IndexesCode4
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question AnsweringCode4
Halu-J: Critique-Based Hallucination JudgeCode4
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented GenerationCode4
R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement LearningCode4
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt OptimizationCode4
Goldfish: Vision-Language Understanding of Arbitrarily Long VideosCode4
Gated Delta Networks: Improving Mamba2 with Delta RuleCode4
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning AgentsCode4
Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text RetrieversCode4
PLAID: An Efficient Engine for Late Interaction RetrievalCode4
Generative Representational Instruction TuningCode4
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality TeachersCode4
Benchmarking Retrieval-Augmented Generation for MedicineCode4
Prompt2Model: Generating Deployable Models from Natural Language InstructionsCode4
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process RewardingCode4
Evaluating Pre-trained Convolutional Neural Networks and Foundation Models as Feature Extractors for Content-based Medical Image RetrievalCode4
A Survey of LLM DATACode4
Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language ModelsCode4
One Embedder, Any Task: Instruction-Finetuned Text EmbeddingsCode4
EasyRAG: Efficient Retrieval-Augmented Generation Framework for Automated Network OperationsCode4
DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming HeadsCode4
FG-CLIP: Fine-Grained Visual and Textual AlignmentCode4
OnPrem.LLM: A Privacy-Conscious Document Intelligence ToolkitCode4
2D Matryoshka Sentence EmbeddingsCode4
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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