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 1001–1025 of 14297 papers

TitleStatusHype
How Vital is the Jurisprudential Relevance: Law Article Intervened Legal Case Retrieval and Matching—0
Rank1: Test-Time Compute for Reranking in Information RetrievalCode2
KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation—0
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting—0
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented SearchersCode2
On Synthetic Data Strategies for Domain-Specific Generative Retrieval—0
Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based InferenceCode0
FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA—0
RankCoT: Refining Knowledge for Retrieval-Augmented Generation through Ranking Chain-of-ThoughtsCode2
Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation—0
Tip of the Tongue Query Elicitation for Simulated EvaluationCode0
Evaluating the Effect of Retrieval Augmentation on Social Biases—0
MegaLoc: One Retrieval to Place Them AllCode2
ATEB: Evaluating and Improving Advanced NLP Tasks for Text Embedding Models—0
Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence—0
Logic Haystacks: Probing LLMs Long-Context Logical Reasoning (Without Easily Identifiable Unrelated Padding)—0
Multimodal Search in Chemical Documents and ReactionsCode0
Language Model Re-rankers are Steered by Lexical Similarities—0
Toward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking—0
LLM-QE: Improving Query Expansion by Aligning Large Language Models with Ranking PreferencesCode1
A Hybrid Approach to Information Retrieval and Answer Generation for Regulatory TextsCode0
MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented GenerationCode0
CodeSwift: Accelerating LLM Inference for Efficient Code Generation—0
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
Optimizing Retrieval-Augmented Generation of Medical Content for Spaced Repetition Learning—0
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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