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 8176–8200 of 14297 papers

TitleStatusHype
MCoT-RE: Multi-Faceted Chain-of-Thought and Re-Ranking for Training-Free Zero-Shot Composed Image Retrieval—0
MCP Safety Training: Learning to Refuse Falsely Benign MCP Exploits using Improved Preference Alignment—0
MCP-Zero: Active Tool Discovery for Autonomous LLM Agents—0
Optimal Projected Variance Group-Sparse Block PCA—0
Group Non-negative Matrix Factorization with Natural Categories for Question Retrieval in Community Question Answer Archives—0
Group Invariant Deep Representations for Image Instance Retrieval—0
MDL-CW: A Multimodal Deep Learning Framework With Cross Weights—0
MDMMT-2: Multidomain Multimodal Transformer for Video Retrieval, One More Step Towards Generalization—0
Group Generalized Mean Pooling for Vision Transformer—0
Grounding Physical Object and Event Concepts Through Dynamic Visual Reasoning—0
Controlling Chat Bot Multi-Document Navigation with the Extended Discourse Trees—0
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning—0
Mean Field Theory in Deep Metric Learning—0
Grounding-MD: Grounded Video-language Pre-training for Open-World Moment Detection—0
Controlled Retrieval-augmented Context Evaluation for Long-form RAG—0
A tool suite for creating question answering benchmarks—0
AlzheimerRAG: Multimodal Retrieval Augmented Generation for PubMed articles—0
Adaptive Co-weighting Deep Convolutional Features For Object Retrieval—0
Grounding Language Model with Chunking-Free In-Context Retrieval—0
Controlled AutoEncoders to Generate Faces from Voices—0
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval—0
Ground Every Sentence: Improving Retrieval-Augmented LLMs with Interleaved Reference-Claim Generation—0
Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study—0
Atomic Fact Decomposition Helps Attributed Question Answering—0
Grounded in Context: Retrieval-Based Method for Hallucination Detection—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