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 9951–10000 of 14297 papers

TitleStatusHype
Local Orthogonal-Group Testing—0
Local Quadruple Pattern: A Novel Descriptor for Facial Image Recognition and Retrieval—0
Local Radon Descriptors for Image Search—0
Local Similarity-Aware Deep Feature Embedding—0
Local versus Global Strategies in Social Query Expansion—0
Location Field Descriptors: Single Image 3D Model Retrieval in the Wild—0
Location reference recognition from texts: A survey and comparison—0
Location retrieval using visible landmarks based qualitative place signatures—0
Location Sensitive Image Retrieval and Tagging—0
LocLinkVis: A Geographic Information Retrieval-Based System for Large-Scale Exploratory Search—0
LoCUS: Learning Multiscale 3D-consistent Features from Posed Images—0
Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval—0
LOC-ZSON: Language-driven Object-Centric Zero-Shot Object Retrieval and Navigation—0
Low-light phase retrieval with implicit generative priors—0
Logical Discrete Graphical Models Must Supplement Large Language Models for Information Synthesis—0
Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture—0
Logical Metonymy in a Distributional Model of Sentence Comprehension—0
Logical segmentation for article extraction in digitized old newspapers—0
Logic Haystacks: Probing LLMs Long-Context Logical Reasoning (Without Easily Identifiable Unrelated Padding)—0
LoGS: Visual Localization via Gaussian Splatting with Fewer Training Images—0
Long Concept Query on Conceptual Taxonomies—0
Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG—0
Long Context Modeling with Ranked Memory-Augmented Retrieval—0
LongEval at CLEF 2025: Longitudinal Evaluation of IR Model Performance—0
LongEval-Retrieval: French-English Dynamic Test Collection for Continuous Web Search Evaluation—0
Long-form Question Answering: An Iterative Planning-Retrieval-Generation Approach—0
Long-Horizon Planning and Execution with Functional Object-Oriented Networks—0
LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs—0
Long-short Term Motion Feature for Action Classification and Retrieval—0
Long-Tail Crisis in Nearest Neighbor Language Models—0
Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions—0
Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory—0
Look Before You Leap: Improving Text-based Person Retrieval by Learning A Consistent Cross-modal Common Manifold—0
Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models—0
Look into the Future: Deep Contextualized Sequential Recommendation—0
LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification—0
LoopITR: Combining Dual and Cross Encoder Architectures for Image-Text Retrieval—0
Loops On Retrieval Augmented Generation (LoRAG)—0
LoRACode: LoRA Adapters for Code Embeddings—0
LoRA-Contextualizing Adaptation of Large Multimodal Models for Long Document Understanding—0
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild—0
LoRE: Logit-Ranked Retriever Ensemble for Enhancing Open-Domain Question Answering—0
Lorentzian Distance Learning—0
Lost in OCR Translation? Vision-Based Approaches to Robust Document Retrieval—0
Lost in Transliteration: Bridging the Script Gap in Neural IR—0
Lost Your Style? Navigating with Semantic-Level Approach for Text-to-Outfit Retrieval—0
Low Complexity Regularized Phase Retrieval—0
Low Compute and Fully Parallel Computer Vision With HashMatch—0
Low-dimensional Query Projection based on Divergence Minimization Feedback Model for Ad-hoc Retrieval—0
Low-frequency Image Deep Steganography: Manipulate the Frequency Distribution to Hide Secrets with Tenacious Robustness—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