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
Retrieval Data Augmentation Informed by Downstream Question Answering Performance—0
Repo4QA: Answering Complex Coding Questions via Dense Retrieval on GitHub Repositories—0
HybriDialogue: An Information-Seeking Dialogue Dataset Grounded on Tabular and Textual Data—0
CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation—0
Modeling Multi-hop Question Answering as Single Sequence Prediction—0
Get Your Model Puzzled: Introducing Crossword-Solving as a New NLP Benchmark—0
Get the Point! Graph Enhanced Candidate Retrieval for Zero-shot Entity Linking—0
Constructing Phrase-level Semantic Labels to Form Multi-GrainedSupervision for Image-Text Retrieval—0
RELiC: Retrieving Evidence for Literary Claims—0
Searching for fingerspelled content in American Sign Language—0
Ask Me Anything in Your Native Language—0
Calibration of Machine Reading Systems at Scale—0
Dynamic Entity Memory Network for Dialogue Relational Triplet Extraction—0
DS-TOD: Efficient Domain Specialization for Task-Oriented Dialog—0
Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment—0
Do We Need to Differentiate Negative Candidates Before Training a Neural Ranker?—0
MATHion: Solving Math Word Problems with Logically Consistent Problems—0
XLTime: A Cross-Lingual Knowledge Transfer Framework for Zero-Shot Low-Resource Language Temporal Expression Extraction—0
Meet Your Favorite Character: Open-domain Chatbot Mimicking Fictional Characters with only a Few Utterances—0
Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models—0
DialFact: A Benchmark for Fact-Checking in Dialogue—0
Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data—0
BERT got a Date: Introducing Transformers to Temporal Tagging—0
Slot Filling for Biomedical Information Extraction—0
Retrieval-based Layer-wise Adaptive Transformer for Source Code Summarization—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