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 7501–7550 of 14297 papers

TitleStatusHype
A Gradient Accumulation Method for Dense Retriever under Memory Constraint—0
Learning Joint Embedding for Cross-Modal Retrieval—0
Event-aware Video Corpus Moment Retrieval—0
EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE—0
Developing a Dataset for Evaluating Approaches for Document Expansion with Images—0
Learning text-to-video retrieval from image captioning—0
EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models—0
EVCap: Retrieval-Augmented Image Captioning with External Visual-Name Memory for Open-World Comprehension—0
Class-agnostic Object Detection—0
Learning the Visualness of Text Using Large Vision-Language Models—0
1-PAGER: One Pass Answer Generation and Evidence Retrieval—0
Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation—0
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning—0
Learning to Cluster Faces via Transformer—0
LLM-Augmented Retrieval: Enhancing Retrieval Models Through Language Models and Doc-Level Embedding—0
Learning to Coordinate Multiple Reinforcement Learning Agents for Diverse Query Reformulation—0
Learning to Decompose Visual Features with Latent Textual Prompts—0
Development of An Android Application for Object Detection Based on Color, Shape, or Local Features—0
Learning to Detect Human-Object Interactions With Knowledge—0
LLM Program Optimization via Retrieval Augmented Search—0
Learning to Embed Multi-Modal Contexts for Situated Conversational Agents—0
Learning to Embed Multi-Modal Contexts for Situated Conversational Agents—0
Learning to embed semantic similarity for joint image-text retrieval—0
Evaluation Set for Slovak News Information Retrieval—0
CLAS: A Machine Learning Enhanced Framework for Exploring Large 3D Design Datasets—0
Learning to Exploit Different Translation Resources for Cross Language Information Retrieval—0
Evaluation of Table Representations to Answer Questions from Tables in Documents : A Case Study using 3GPP Specifications—0
Evaluation of some Information Retrieval models for Gujarati Ad hoc Monolingual Tasks—0
A Gold Standard for CLIR evaluation in the Organic Agriculture Domain—0
Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language—0
Clarification of Video Retrieval Query Results by the Automated Insertion of Supporting Shots—0
Learning to Hash-tag Videos with Tag2Vec—0
Learning to Hash with Binary Reconstructive Embeddings—0
Learning to Hash with Graph Neural Networks for Recommender Systems—0
Learning to hash with semantic similarity metrics and empirical KL divergence—0
Learning to Interpret and Describe Abstract Scenes—0
Evaluation of RAG Metrics for Question Answering in the Telecom Domain—0
Evaluation of quadratic phase hologram calculation algorithms in the Fourier regime—0
A Retrieval Framework and Implementation for Electronic Documents with Similar Layouts—0
Learning to Link—0
D-Graph: AI-Assisted Design Concept Exploration Graph—0
BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models—0
A Tale of Two Efficient and Informative Negative Sampling Distributions—0
LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning—0
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank Metrics—0
Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow—0
Evaluation of medium-large Language Models at zero-shot closed book generative question answering—0
Evaluation of Information Retrieval Systems Using Structural Equation Modelling—0
DIABLO: Dictionary-based Attention Block for Deep Metric Learning—0
Evaluation of drain, a deep-learning approach to rain retrieval from gpm passive microwave radiometer—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