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 4626–4650 of 14297 papers

TitleStatusHype
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks—0
Revisiting Sparse Retrieval for Few-shot Entity LinkingCode0
MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal AdapterCode1
A Read-and-Select Framework for Zero-shot Entity LinkingCode0
Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher—0
Noise-robust latent vector reconstruction in ptychography using deep generative models—0
Position Interpolation Improves ALiBi ExtrapolationCode2
REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language ModelsCode1
Retrieve-Cluster-Summarize: An Alternative to End-to-End Training for Query-specific Article Generation—0
Open-ended Commonsense Reasoning with Unrestricted Answer Scope—0
From Relevance to Utility: Evidence Retrieval with Feedback for Fact VerificationCode0
Towards Safer Operations: An Expert-involved Dataset of High-Pressure Gas Incidents for Preventing Future FailuresCode0
Understanding Retrieval Augmentation for Long-Form Question Answering—0
CLARA: Multilingual Contrastive Learning for Audio Representation AcquisitionCode1
CIR at the NTCIR-17 ULTRE-2 Task—0
Emptying the Ocean with a Spoon: Should We Edit Models?—0
Simulating Users in Interactive Web Table RetrievalCode0
A Comprehensive Evaluation of Large Language Models on Legal Judgment PredictionCode1
A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge—0
Balance Act: Mitigating Hubness in Cross-Modal Retrieval with Query and Gallery BanksCode0
Heterogenous Memory Augmented Neural NetworksCode0
KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language ModelsCode1
On Coherence-based Predictors for Dense Query Performance Prediction—0
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionCode4
Towards reducing hallucination in extracting information from financial reports using Large 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