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 7251–7300 of 14297 papers

TitleStatusHype
A Review on Image Texture Analysis Methods—0
Learning Visual Features from Snapshots for Web Search—0
DeepTopPush: Simple and Scalable Method for Accuracy at the Top—0
LawngNLI: a multigranular, long-premise NLI benchmark for evaluating models’ in-domain generalization from short to long contexts—0
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA—0
LawSum: A weakly supervised approach for Indian Legal Document Summarization—0
Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks—0
Classifying Peace in Global Media Using RAG and Intergroup Reciprocity—0
Layer-wise Investigation of Large-Scale Self-Supervised Music Representation Models—0
Evidence to Generate (E2G): A Single-agent Two-step Prompting for Context Grounded and Retrieval Augmented Reasoning—0
Classifying magnetic resonance image modalities with convolutional neural networks—0
LayoutCoT: Unleashing the Deep Reasoning Potential of Large Language Models for Layout Generation—0
A Review of Speaker Diarization: Recent Advances with Deep Learning—0
EVIDENCEMINER: Textual Evidence Discovery for Life Sciences—0
Deep-Unrolling Multidimensional Harmonic Retrieval Algorithms on Neuromorphic Hardware—0
Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation—0
Classification Tree Diagrams in Health Informatics Applications—0
Evidence Contextualization and Counterfactual Attribution for Conversational QA over Heterogeneous Data with RAG Systems—0
LDOP: Local Directional Order Pattern for Robust Face Retrieval—0
Evidence-based Trustworthiness—0
Classification or Generation? Understanding Paradigm Shift for Knowledge-Intensive Tasks—0
LEAD: Liberal Feature-based Distillation for Dense Retrieval—0
LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender System—0
LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models—0
A Review of Repository Level Prompting for LLMs—0
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings—0
Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search—0
EveTAR: Building a Large-Scale Multi-Task Test Collection over Arabic Tweets—0
Everything Can Be Described in Words: A Simple Unified Multi-Modal Framework with Semantic and Temporal Alignment—0
Classification on Sentence Embeddings for Legal Assistance—0
A Review of Image Retrieval Techniques: Data Augmentation and Adversarial Learning Approaches—0
Learn-by-interact: A Data-Centric Framework for Self-Adaptive Agents in Realistic Environments—0
Learned Index with Dynamic—0
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection—0
Learned versus Hand-Designed Feature Representations for 3d Agglomeration—0
Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions—0
ASR-enhanced Multimodal Representation Learning for Cross-Domain Product Retrieval—0
Learning a Disentangled Embedding for Monocular 3D Shape Retrieval and Pose Estimation—0
Learning a Facial Expression Embedding Disentangled From Identity—0
Deformable Voxel Grids for Shape Comparisons—0
Classification of sparsely labeled spatio-temporal data through semi-supervised adversarial learning—0
Learning Aligned Cross-Modal Representations from Weakly Aligned Data—0
Learning Alternative Name Spellings—0
Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems—0
DEFT2018 : recherche d'information et analyse de sentiments dans des tweets concernant les transports en \^Ile de France (DEFT2018 : Information Retrieval and Sentiment Analysis in Tweets about Public Transportation in \^Ile de France Region )—0
Learning Translation Models from Monolingual Continuous Representations—0
Learning and Crafting for the Wide Multiple Baseline Stereo—0
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks—0
Learning and Retrieval from Prior Data for Skill-based Imitation Learning—0
Event Temporal Relation Extraction based on Retrieval-Augmented on LLMs—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