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 13851–13900 of 14297 papers

TitleStatusHype
Recognizing Descriptive Wikipedia Categories for Historical Figures—0
RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance—0
RaFe: Ranking Feedback Improves Query Rewriting for RAG—0
Recognizing Families through Images with Pretrained Encoder—0
Using GPT Models for Qualitative and Quantitative News Analytics in the 2024 US Presidental Election Process—0
Recommendation or Discrimination?: Quantifying Distribution Parity in Information Retrieval Systems—0
Recommender Systems: A Primer—0
Recommender Systems Notation: Proposed Common Notation for Teaching and Research—0
RAEE: A Robust Retrieval-Augmented Early Exiting Framework for Efficient Inference—0
Recommending best course of treatment based on similarities of prognostic markers—0
Recommending Research Papers to Chemists: A Specialized Interface for Chemical Entity Exploration—0
RAD: Retrieval-Augmented Decision-Making of Meta-Actions with Vision-Language Models in Autonomous Driving—0
Reconciling Methodological Paradigms: Employing Large Language Models as Novice Qualitative Research Assistants in Talent Management Research—0
Using In-Context Learning to Improve Dialogue Safety—0
Radon-Gabor Barcodes for Medical Image Retrieval—0
Radon Features and Barcodes for Medical Image Retrieval via SVM—0
Recourse for reclamation: Chatting with generative language models—0
Recovering Variable Names for Minified Code with Usage Contexts—0
How Much Training Data is Memorized in Overparameterized Autoencoders? An Inverse Problem Perspective on Memorization Evaluation—0
Recovery under Side Constraints—0
RA-DIT: Retrieval-Augmented Dual Instruction Tuning—0
Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors—0
RadIR: A Scalable Framework for Multi-Grained Medical Image Retrieval via Radiology Report Mining—0
Recurrent Neural Network Encoder with Attention for Community Question Answering—0
Recursive Abstractive Processing for Retrieval in Dynamic Datasets—0
Recursive Distillation for Open-Set Distributed Robot Localization—0
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence—0
Red Dragon AI at TextGraphs 2021 Shared Task: Multi-Hop Inference Explanation Regeneration by Matching Expert Ratings—0
ReDecode Framework for Iterative Improvement in Paraphrase Generation—0
ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability—0
Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness—0
Redefining Information Retrieval of Structured Database via Large Language Models—0
Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment—0
Radiological images and machine learning: trends, perspectives, and prospects—0
Radial Velocity Retrieval for Multichannel SAR Moving Targets with Time-Space Doppler De-ambiguity—0
Rethinking preventing class-collapsing in metric learning with margin-based losses—0
Reducing Class Collapse in Metric Learning with Easy Positive Sampling—0
Reducing Distraction in Long-Context Language Models by Focused Learning—0
Reducing hallucination in structured outputs via Retrieval-Augmented Generation—0
Reducing Hallucinations in Language Model-based SPARQL Query Generation Using Post-Generation Memory Retrieval—0
Reducing Noise from Competing Neighbours: Word Retrieval with Lateral Inhibition in Multilink—0
Radial Line Fourier Descriptor for Historical Handwritten Text Representation—0
RACOON: An LLM-based Framework for Retrieval-Augmented Column Type Annotation with a Knowledge Graph—0
Reducing the climate impact of data portals: a case study—0
Reducing the Footprint of Multi-Vector Retrieval with Minimal Performance Impact via Token Pooling—0
Reducing the Vision and Language Bias for Temporal Sentence Grounding—0
Redundancy Localization for the Conversationalization of Unstructured Responses—0
Reference Product Search—0
References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulation—0
Open Set Chinese Character Recognition using Multi-typed Attributes—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