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 13351–13400 of 14297 papers

TitleStatusHype
Two LRL \& Distractor Corpora from Web Information Retrieval and a Small Case Study in Language Identification without Training Corpora—0
Two-person interaction detection using body-pose features and multiple instance learning—0
Overview of the TREC 2019 Fair Ranking Track—0
Two-Stage Document Length Normalization for Information Retrieval—0
Two-Stage Hashing for Fast Document Retrieval—0
Two-Stage Triplet Loss Training with Curriculum Augmentation for Audio-Visual Retrieval—0
Wikipedia Text Reuse: Within and Without—0
Zero-Shot Listwise Document Reranking with a Large Language Model—0
Two-Stream Networks for Object Segmentation in Videos—0
Zeroshot Listwise Learning to Rank Algorithm for Recommendation—0
One Pic is All it Takes: Poisoning Visual Document Retrieval Augmented Generation with a Single Image—0
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries—0
WindTunnel -- A Framework for Community Aware Sampling of Large Corpora—0
Overview of the Third Workshop on Scholarly Document Processing—0
UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training—0
Zero-shot Medical Entity Retrieval without Annotation: Learning From Rich Knowledge Graph Semantics—0
UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)—0
Overview of the Second Workshop on Scholarly Document Processing—0
Overview of Stemming Algorithms for Indian and Non-Indian Languages—0
Overview of LiLAS 2020 -- Living Labs for Academic Search—0
Overparameterized Neural Networks Can Implement Associative Memory—0
Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in QA Agents—0
UFO: A UniFied TransfOrmer for Vision-Language Representation Learning—0
Winning Solution For Meta KDD Cup' 24—0
Overcoming the Long Tail Problem: A Case Study on CO2-Footprint Estimation of Recipes using Information Retrieval—0
UGent-T2K at the 2nd DialDoc Shared Task: A Retrieval-Focused Dialog System Grounded in Multiple Documents—0
UGIF: UI Grounded Instruction Following—0
Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrieval—0
Overcoming low-utility facets for complex answer retrieval—0
Overcoming LLM Challenges using RAG-Driven Precision in Coffee Leaf Disease Remediation—0
Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts—0
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models—0
Outfit Completion via Conditional Set Transformation—0
Wireless Image Retrieval at the Edge—0
WisdomBot: Tuning Large Language Models with Artificial Intelligence Knowledge—0
OSLAT: Open Set Label Attention Transformer for Medical Entity Retrieval and Span Extraction—0
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion—0
OSCAR: Online Soft Compression And Reranking—0
WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models—0
Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer—0
UlyssesNER-Br: A Corpus of Brazilian Legislative Documents for Named Entity Recognition—0
MoSE: Hierarchical Self-Distillation Enhances Early Layer Embeddings—0
Orthogonal Matrix Retrieval in Cryo-Electron Microscopy—0
UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation—0
UMEC: Unified model and embedding compression for efficient recommendation systems—0
UMFuse: Unified Multi View Fusion for Human Editing applications—0
Orientation Invariant Feature Embedding and Spatial Temporal Regularization for Vehicle Re-Identification—0
Orientation covariant aggregation of local descriptors with embeddings—0
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation—0
Unambiguous Text Localization and Retrieval for Cluttered Scenes—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