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
Long-Context Inference with Retrieval-Augmented Speculative DecodingCode1
Joint Fusion and Encoding: Advancing Multimodal Retrieval from the Ground Up—0
Lightweight Contrastive Distilled Hashing for Online Cross-modal Retrieval—0
Mixture of Structural-and-Textual Retrieval over Text-rich Graph Knowledge BasesCode1
Bridging Legal Knowledge and AI: Retrieval-Augmented Generation with Vector Stores, Knowledge Graphs, and Hierarchical Non-negative Matrix FactorizationCode1
From Retrieval to Generation: Comparing Different Approaches—0
Granite Embedding Models—0
PhantomWiki: On-Demand Datasets for Reasoning and Retrieval EvaluationCode1
Do Retrieval-Augmented Language Models Adapt to Varying User Needs?—0
RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings—0
SCA3D: Enhancing Cross-modal 3D Retrieval via 3D Shape and Caption Paired Data AugmentationCode0
Hierarchical corpus encoder: Fusing generative retrieval and dense indices—0
OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment—0
Trustworthy Answers, Messier Data: Bridging the Gap in Low-Resource Retrieval-Augmented Generation for Domain Expert Systems—0
On the Importance of Text Preprocessing for Multimodal Representation Learning and Pathology Report Generation—0
Agentic Mixture-of-Workflows for Multi-Modal Chemical Search—0
Agent-centric Information Access—0
Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in QA Agents—0
A 106K Multi-Topic Multilingual Conversational User Dataset with Emoticons—0
Automated Code Generation and Validation for Software Components of Microcontrollers—0
Efficient Federated Search for Retrieval-Augmented Generation—0
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining—0
Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning—0
Uncertainty Quantification in Retrieval Augmented Question AnsweringCode0
Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based InferenceCode0
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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