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 976–1000 of 14297 papers

TitleStatusHype
Evaluating Retrieval Quality in Retrieval-Augmented GenerationCode1
How Does the Textual Information Affect the Retrieval of Multimodal In-Context Learning?Code1
Dubo-SQL: Diverse Retrieval-Augmented Generation and Fine Tuning for Text-to-SQLCode1
Length Generalization of Causal Transformers without Position EncodingCode1
Improving Composed Image Retrieval via Contrastive Learning with Scaling Positives and NegativesCode1
SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMsCode1
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape ReconstructionCode1
LLMs4OM: Matching Ontologies with Large Language ModelsCode1
Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question AnsweringCode1
ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidenceCode1
Memory Sharing for Large Language Model based AgentsCode1
Knowledge-enhanced Visual-Language Pretraining for Computational PathologyCode1
Task-Driven Exploration: Decoupling and Inter-Task Feedback for Joint Moment Retrieval and Highlight DetectionCode1
Not All Contexts Are Equal: Teaching LLMs Credibility-aware GenerationCode1
Semantically-correlated memories in a dense associative modelCode1
RAR-b: Reasoning as Retrieval BenchmarkCode1
Retrieval-Augmented Open-Vocabulary Object DetectionCode1
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringCode1
Outlier-Efficient Hopfield Layers for Large Transformer-Based ModelsCode1
CONFLARE: CONFormal LArge language model REtrievalCode1
How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?Code1
RAT: Retrieval-Augmented Transformer for Click-Through Rate PredictionCode1
CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systemsCode1
Query Performance Prediction using Relevance Judgments Generated by Large Language ModelsCode1
Generative Retrieval as Multi-Vector Dense RetrievalCode1
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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