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 6751–6800 of 14297 papers

TitleStatusHype
Recitation-Augmented Language ModelsCode1
ThinkSum: Probabilistic reasoning over sets using large language models—0
On Background Bias in Deep Metric LearningCode0
A Framework for Web Services Retrieval Using Bio Inspired Clustering—0
SpeechCLIP: Integrating Speech with Pre-Trained Vision and Language ModelCode1
Complexity-Based Prompting for Multi-Step Reasoning—0
SPARC: Sparse Render-and-Compare for CAD model alignment in a single RGB imageCode1
Contrastive Audio-Visual Masked AutoencoderCode2
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval—0
Long-Term Person Re-identification with Dramatic Appearance Change: Algorithm and BenchmarkCode1
Mitigating Data Shift of Biomedical Research Articles for Information Retrieval and Semantic Indexing—0
Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving—0
Multi-objective Representation Learning for Scientific Document RetrievalCode0
Overview of the Third Workshop on Scholarly Document Processing—0
Query Processing and Optimization for a Custom Retrieval LanguageCode0
TextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models—0
DocQueryNet: Value Retrieval with Arbitrary Queries for Form-like DocumentsCode1
Dense Template Retrieval for Customer Support—0
QualiAssistant: Extracting Qualia Structures from Texts—0
MuSeCLIR: A Multiple Senses and Cross-lingual Information Retrieval DatasetCode0
Towards Robust Neural Retrieval with Source Domain Synthetic Pre-Finetuning—0
Augmentation, Retrieval, Generation: Event Sequence Prediction with a Three-Stage Sequence-to-Sequence Approach—0
Virtual Knowledge Graph Construction for Zero-Shot Domain-Specific Document RetrievalCode0
Logical Form Generation via Multi-task Learning for Complex Question Answering over Knowledge BasesCode1
Label Smoothing for Text Mining—0
Semantic Content Prediction for Generating Interviewing Dialogues to Elicit Users’ Food Preferences—0
Repo4QA: Answering Coding Questions via Dense Retrieval on GitHub RepositoriesCode0
Reciprocal Learning of Knowledge Retriever and Response Ranker for Knowledge-Grounded Conversations—0
Event Extraction in Video Transcripts—0
CitRet: A Hybrid Model for Cited Text Span RetrievalCode0
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss—0
Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple TasksCode1
Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-SupervisionCode0
SmallCap: Lightweight Image Captioning Prompted with Retrieval AugmentationCode1
DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge BasesCode1
Zero-Shot Retrieval with Search Agents and Hybrid Environments—0
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training—0
Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval—0
Diffusion Posterior Sampling for General Noisy Inverse ProblemsCode2
Re-Imagen: Retrieval-Augmented Text-to-Image Generator—0
REST: REtrieve & Self-Train for generative action recognition—0
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing—0
Evaluating Research Dataset Recommendations in a Living Lab—0
Multi-stage Information Retrieval for Vietnamese Legal Texts—0
Mr. Right: Multimodal Retrieval on Representation of ImaGe witH TextCode1
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative ModelingCode1
Weighted Contrastive HashingCode0
TokenFlow: Rethinking Fine-grained Cross-modal Alignment in Vision-Language Retrieval—0
Audio Retrieval with WavText5K and CLAP TrainingCode1
SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image RetrievalCode0
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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