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 10751–10800 of 14297 papers

TitleStatusHype
Conversational Search for Learning Technologies—0
Resolving the Scope of Speculation and Negation using Transformer-Based ArchitecturesCode0
Topical Result Caching in Web Search Engines—0
Weakly Supervised Visual Semantic ParsingCode1
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model—0
Measuring Diversity in Heterogeneous Information Networks—0
Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks—0
Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text SegmentationCode1
Video Cloze Procedure for Self-Supervised Spatio-Temporal LearningCode1
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions—0
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual GeneralisationCode1
Retrieval Augmented Language Model Pre-Training—0
Dynamic 3-D measurement based on fringe-to-fringe transformation using deep learning—0
Image retrieval approach based on local texture information derived from predefined patterns and spatial domain information—0
Teaching a New Dog Old Tricks: Resurrecting Multilingual Retrieval Using Zero-shot LearningCode0
Robust Cross-lingual Embeddings from Parallel SentencesCode0
Report on the SIGIR 2019 Workshop on eCommerce (ECOM19)—0
N-gram Statistical Stemmer for Bangla CorpusCode0
Harnessing Evolution of Multi-Turn Conversations for Effective Answer RetrievalCode0
Multimodal Prediction based on Graph Representations—0
A Machine Learning Framework for Authorship Identification From Texts—0
End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language ModelsCode0
Report on the First HIPstIR Workshop on the Future of Information Retrieval—0
Fashion Outfit Complementary Item RetrievalCode0
Macaw: An Extensible Conversational Information Seeking PlatformCode0
Curriculum Learning Strategies for IR: An Empirical Study on Conversation Response RankingCode0
iASiS Open Data Graph: Automated Semantic Integration of Disease-Specific KnowledgeCode0
DeepHashing using TripletLoss—0
Chinese Named Entity Recognition Augmented with Lexicon MemoryCode0
Topology Learning of Linear Dynamical Systems with Latent Nodes using Matrix Decomposition—0
Semantic Segmentation for Compound figures—0
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data ScienceCode0
Efficient Bitmap-based Indexing and Retrieval of Similarity Search Image Queries—0
Cross-Batch Memory for Embedding LearningCode1
Deep-learning-based classification and retrieval of components of a process plant from segmented point clouds—0
End-to-End Learning of Visual Representations from Uncurated Instructional VideosCode1
SetRank: Learning a Permutation-Invariant Ranking Model for Information RetrievalCode0
Lifelong learning for text retrieval and recognition in historical handwritten document collections—0
Introducing MANtIS: a novel Multi-Domain Information Seeking Dialogues DatasetCode0
Managing Machine Learning Workflow ComponentsCode0
Duet at TREC 2019 Deep Learning TrackCode0
Phase Retrieval Using Conditional Generative Adversarial NetworksCode0
Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking ResultsCode0
Learning Disentangled Representations via Mutual Information EstimationCode0
Attentive Representation Learning with Adversarial Training for Short Text Clustering—0
Exploring the Ideal Depth of Neural Network when Predicting Question Deletion on Community Question Answering—0
ICDAR 2019 Competition on Image Retrieval for Historical Handwritten DocumentsCode0
Optimizing Rank-based Metrics with Blackbox DifferentiationCode1
Geometric Capsule Autoencoders for 3D Point Clouds—0
Document Network Embedding: Coping for Missing Content and Missing Links—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