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 9201–9250 of 14297 papers

TitleStatusHype
Build Fast and Accurate Lemmatization for Arabic—0
Building a Dataset of Multilingual Cognates for the Romanian Lexicon—0
Building A Large Concept Bank for Representing Events in Video—0
Building a Large-scale Multimodal Knowledge Base System for Answering Visual Queries—0
Building a Learning Database for the Neural Network Retrieval of Sea Surface Salinity from SMOS Brightness Temperatures—0
Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning—0
Building an Efficient Multilingual Non-Profit IR System for the Islamic Domain Leveraging Multiprocessing Design in Rust—0
Building an Enhanced Autoregressive Document Retriever Leveraging Supervised Contrastive Learning—0
Building a Production Model for Retrieval-Based Chatbots—0
Building a Question Answering System for the Manufacturing Domain—0
Building Cross-Sectional Systematic Strategies By Learning to Rank—0
Building Discourse Parser for Thirukkural—0
Building Evaluation Datasets for Consumer-Oriented Information Retrieval—0
Building Evaluation Datasets for Cultural Microblog Retrieval—0
Building Extractive Question Answering System to Support Human-AI Health Coaching Model for Sleep Domain—0
Building Interpretable and Reliable Open Information Retriever for New Domains Overnight—0
Building Large Chinese Corpus for Spoken Dialogue Research in Specific Domains—0
Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model—0
Building of Networks of Natural Hierarchies of Terms Based on Analysis of Texts Corpora—0
Building Retrieval Systems for the ClueWeb22-B Corpus—0
Building Subject-aligned Comparable Corpora and Mining it for Truly Parallel Sentence Pairs—0
Building Trustworthy AI: Transparent AI Systems via Large Language Models, Ontologies, and Logical Reasoning (TranspNet)—0
Building Vision-Language Models on Solid Foundations with Masked Distillation—0
BURT: BERT-inspired Universal Representation from Learning Meaningful Segment—0
Business Entity Entropy—0
BUTTER: A Representation Learning Framework for Bi-directional Music-Sentence Retrieval and Generation—0
ByteCover3: Accurate Cover Song Identification on Short Queries—0
C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval—0
C^3DRec: Cloud-Client Cooperative Deep Learning for Temporal Recommendation in the Post-GDPR Era—0
C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation—0
Cache-Aided Multi-User Private Information Retrieval using PDAs—0
Cache-Augmented Latent Topic Language Models for Speech Retrieval—0
Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation—0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation—0
Caching and Reproducibility: Making Data Science experiments faster and FAIRer—0
Caching Historical Embeddings in Conversational Search—0
CAD-NeRF: Learning NeRFs from Uncalibrated Few-view Images by CAD Model Retrieval—0
CAFE: Retrieval Head-based Coarse-to-Fine Information Seeking to Enhance Multi-Document QA Capability—0
CAIBC: Capturing All-round Information Beyond Color for Text-based Person Retrieval—0
CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents—0
CAISSON: Concept-Augmented Inference Suite of Self-Organizing Neural Networks—0
Calibrated Decision-Making through LLM-Assisted Retrieval—0
Calibrated neighborhood aware confidence measure for deep metric learning—0
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification—0
Calibrating Probabilistic Embeddings for Cross-Modal Retrieval—0
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning—0
Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning—0
Calibration of Machine Reading Systems at Scale—0
Calibration of Machine Reading Systems at Scale—0
CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition—0
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All datasetsQuora Question PairsHotpotQANatural QuestionsOK-VQAInfoSeekMVKPolyvorePubMedQAPubMedQA corpus with metadataToolLensคลิปไวรัล!! ไอซ์ ปรีชญา ลืมปิดไลฟ์สดตอนอาบน้ำ ถูกแชร์กระหึ่มเน็ต

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