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 7901–7925 of 14297 papers

TitleStatusHype
Modeling Exemplification in Long-form Question Answering via Retrieval—0
How do QA models combine knowledge from LM and 100 passages?—0
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction—0
A Text-Image Pair Is not Enough: Language-Vision Relation Inference with Auxiliary Modality Translation—0
Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies—0
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?—0
Revisiting the Roles of “Text” in Text Games—0
Boosted Dense Retriever—0
Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents—0
Multi2WOZ: A Robust Multilingual Dataset and Conversational Pretraining for Task-Oriented Dialog—0
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
Learning Cross-Lingual IR from an English Retriever—0
An Encoder Attribution Analysis for Dense Passage Retriever in Open-Domain Question Answering—0
Knowledge Base Index Compression via Dimensionality and Precision Reduction—0
Re2G: Retrieve, Rerank, Generate—0
Data Augmentation for Biomedical Factoid Question Answering—0
Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking—0
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval—0
Measuring Word-Context Biases in Lexical Semantic Datasets—0
CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning—0
Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer—0
Practical Dataless Text Classification Through Dense Retrieval—0
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document—0
Open Domain Response Generation Guided by Retrieved Conversations—0
Exploring the Value of Multi-View Learning for Session-Aware Query Representation—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