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 1776–1800 of 14297 papers

TitleStatusHype
Cross-Modal Retrieval with Partially Mismatched PairsCode1
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP TasksCode1
MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language ModelCode1
A Deep Recurrent Survival Model for Unbiased RankingCode1
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and DataCode1
Cross-modal Retrieval with Noisy Correspondence via Consistency Refining and MiningCode1
Cross Modal Retrieval with Querybank NormalisationCode1
CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language PairsCode1
Benchmarking Image Retrieval for Visual LocalizationCode1
CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQLCode1
An Empirical Comparison of Instance Attribution Methods for NLPCode1
Cross-Modal Retrieval: A Systematic Review of Methods and Future DirectionsCode1
Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image RetrievalCode1
MUGEN: A Playground for Video-Audio-Text Multimodal Understanding and GENerationCode1
Cross-modal Contrastive Learning for Speech TranslationCode1
Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image RetrievalCode1
Cross-modal Retrieval for Knowledge-based Visual Question AnsweringCode1
Cross-Lingual Cross-Modal Retrieval with Noise-Robust LearningCode1
Multi-Label Cross-Modal RetrievalCode1
Cross-Modal Adapter for Text-Video RetrievalCode1
Benchmarking Retrieval-Augmented Multimomal Generation for Document Question AnsweringCode1
An Empirical Study of End-to-End Video-Language Transformers with Masked Visual ModelingCode1
Benchmarking Robustness of Text-Image Composed RetrievalCode1
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge GeneratorsCode1
Cross-Modal Retrieval for Motion and Text via DopTriple LossCode1
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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