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 3551–3575 of 14297 papers

TitleStatusHype
Dwell in the Beginning: How Language Models Embed Long Documents for Dense RetrievalCode0
Assisting humans in complex comparisons: automated information comparison at scale—0
Assessing the quality of information extraction—0
A Comparison of Methods for Evaluating Generative IRCode0
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringCode1
Outlier-Efficient Hopfield Layers for Large Transformer-Based ModelsCode1
GenQREnsemble: Zero-Shot LLM Ensemble Prompting for Generative Query Reformulation—0
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield ModelsCode0
CONFLARE: CONFormal LArge language model REtrievalCode1
How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?Code1
Embedding-Informed Adaptive Retrieval-Augmented Generation of Large Language Models—0
Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers—0
A Coupled Neural Field Model for the Standard Consolidation Theory—0
Enhancing Cross-lingual Sentence Embedding for Low-resource Languages with Word Alignment—0
KnowHalu: Hallucination Detection via Multi-Form Knowledge Based Factual CheckingCode2
MatAtlas: Text-driven Consistent Geometry Texturing and Material Assignment—0
uTeBC-NLP at SemEval-2024 Task 9: Can LLMs be Lateral Thinkers?Code0
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support ConversationCode0
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison—0
Efficient Multi-Vector Dense Retrieval Using Bit VectorsCode2
A Comprehensive Survey on AI-based Methods for Patents—0
RAT: Retrieval-Augmented Transformer for Click-Through Rate PredictionCode1
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt OptimizationCode4
FraGNNet: A Deep Probabilistic Model for Mass Spectrum Prediction—0
Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models—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