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 8051–8100 of 14297 papers

TitleStatusHype
Are Neural Ranking Models Robust?—0
Document Visual Question Answering Challenge 2020—0
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning—0
Do deep neural networks possess concept space grid cells?—0
MICRON: Multigranular Interaction for Contextualizing RepresentatiON in Non-factoid Question Answering—0
Evaluating a Generative Adversarial Framework for Information Retrieval—0
Magic Mushroom: A Customizable Benchmark for Fine-grained Analysis of Retrieval Noise Erosion in RAG Systems—0
Does RAG Really Perform Bad For Long-Context Processing?—0
MAGMaR Shared Task System Description: Video Retrieval with OmniEmbed—0
Magnushammer: A Transformer-Based Approach to Premise Selection—0
Maia: A Real-time Non-Verbal Chat for Human-AI Interaction—0
MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation—0
Aggregated Wasserstein Metric and State Registration for Hidden Markov Models—0
Wiping out the limitations of Large Language Models -- A Taxonomy for Retrieval Augmented Generation—0
A Computational Inflection for Scientific Discovery—0
Microblog Retrieval for Post-Disaster Relief: Applying and Comparing Neural IR Models—0
MicroNN: An On-device Disk-resident Updatable Vector Database—0
Making Better Use of Edges via Perceptual Grouping—0
DOGR: Leveraging Document-Oriented Contrastive Learning in Generative Retrieval—0
Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking—0
Making Information Seeking Easier: An Improved Pipeline for Conversational Search—0
Making Large Language Models A Better Foundation For Dense Retrieval—0
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking—0
Brainish: Formalizing A Multimodal Language for Intelligence and Consciousness—0
Chinese Movie Dialogue Question Answering Dataset—0
Making question answering more robust through relevant context selection—0
MIA 2022 Shared Task Submission: Leveraging Entity Representations, Dense-Sparse Hybrids, and Fusion-in-Decoder for Cross-Lingual Question Answering—0
Estimation of Speaking Style in Speech Corpora Focusing on speech transcriptions—0
Are manual annotations necessary for statutory interpretations retrieval?—0
MIaS: Math-Aware Retrieval in Digital Mathematical Libraries—0
Mamba Retriever: Utilizing Mamba for Effective and Efficient Dense Retrieval—0
DOLPHIn - Dictionary Learning for Phase Retrieval—0
MAMO: Masked Multimodal Modeling for Fine-Grained Vision-Language Representation Learning—0
Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling—0
Domain Adaptation for Dense Retrieval through Self-Supervision by Pseudo-Relevance Labeling—0
mAnI: Movie Amalgamation using Neural Imitation—0
MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment—0
MAP: Microblogging Assisted Profiling of TV Shows—0
Estimating the Usefulness of Clarifying Questions and Answers for Conversational Search—0
Estimating Robust Query Models with Convex Optimization—0
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese—0
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval—0
Mapping Unparalleled Clinical Professional and Consumer Languages with Embedding Alignment—0
Mapping Visual Features to Semantic Profiles for Retrieval in Medical Imaging—0
MapQA: Open-domain Geospatial Question Answering on Map Data—0
MARAGE: Transferable Multi-Model Adversarial Attack for Retrieval-Augmented Generation Data Extraction—0
MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning—0
MARAGS: A Multi-Adapter System for Multi-Task Retrieval Augmented Generation Question Answering—0
mARC: Memory by Association and Reinforcement of Contexts—0
Estimating Personal Model Parameters from Utterances in Model-based Reminiscence—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