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 14151–14200 of 14297 papers

TitleStatusHype
Retrieval and Localization with Observation Constraints—0
Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy—0
Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models—0
Query Lattice for Translation Retrieval—0
Querying Across Genres for Medical Claims in News—0
Retrieval Augmentation for T5 Re-ranker using External Sources—0
Retrieval Augmentation Reduces Hallucination in Conversation—0
Open Domain Response Generation Guided by Retrieved Conversations—0
Retrieval Augmentation via User Interest Clustering—0
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining—0
Retrieval-Augmented Approach for Unsupervised Anomalous Sound Detection and Captioning without Model Training—0
Retrieval-Augmented Audio Deepfake Detection—0
Retrieval-Augmented Chain-of-Thought in Semi-structured Domains—0
Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT models—0
Retrieval Augmented Classification for Long-Tail Visual Recognition—0
On consistent vertex nomination schemes—0
Retrieval-augmented code completion for local projects using large language models—0
Query Generation with External Knowledge for Dense Retrieval—0
Retrieval-Augmented Code Generation for Universal Information Extraction—0
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft—0
Retrieval-Augmented Controllable Review Generation—0
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples—0
Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples—0
Retrieval Augmented Correction of Named Entity Speech Recognition Errors—0
Retrieval Augmented Cross-Modal Tag Recommendation in Software Q&A Sites—0
Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks—0
Retrieval Augmented Decision-Making: A Requirements-Driven, Multi-Criteria Framework for Structured Decision Support—0
Query Generation for Patent Retrieval with Keyword Extraction based on Syntactic Features—0
Query Generation for Multimodal Documents—0
Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization—0
Query-free Clothing Retrieval via Implicit Relevance Feedback—0
Query Focused Multi-Document Summarization with Distant Supervision—0
Query Exposure Prediction for Groups of Documents in Rankings—0
Retrieval-Augmented Egocentric Video Captioning—0
Retrieval-augmented Encoders for Extreme Multi-label Text Classification—0
Retrieval Augmented End-to-End Spoken Dialog Models—0
Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments—0
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models—0
Retrieval-Augmented Fine-Tuning With Preference Optimization For Visual Program Generation—0
Retrieval-augmented Generation across Heterogeneous Knowledge—0
Query Expansion with Locally-Trained Word Embeddings—0
Query expansion with artificially generated texts—0
Retrieval Augmented Generation-Based Incident Resolution Recommendation System for IT Support—0
Retrieval Augmented Generation-based Large Language Models for Bridging Transportation Cybersecurity Legal Knowledge Gaps—0
Open-Domain Question Answering with Pre-Constructed Question Spaces—0
Query Expansion Using Contextual Clue Sampling with Language Models—0
Retrieval-Augmented Generation by Evidence Retroactivity in LLMs—0
Retrieval Augmented Generation Evaluation for Health Documents—0
Query expansion techniques for information retrieval: A survey—0
Query Expansion Strategy based on Pseudo Relevance Feedback and Term Weight Scheme for Monolingual Retrieval—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