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 4301–4350 of 14297 papers

TitleStatusHype
RGNet: A Unified Clip Retrieval and Grounding Network for Long VideosCode1
RecJPQ: Training Large-Catalogue Sequential RecommendersCode1
Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping—0
Survey on Memory-Augmented Neural Networks: Cognitive Insights to AI Applications—0
Dense X Retrieval: What Retrieval Granularity Should We Use?Code1
Dynamic Weighted Combiner for Mixed-Modal Image RetrievalCode0
The performance of multiple language models in identifying offensive language on social media—0
Quantum Private Information Retrieval from Coded Storage Systems—0
Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning—0
mir_ref: A Representation Evaluation Framework for Music Information Retrieval TasksCode1
DevBots can co-design APIs—0
Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs—0
ESPN: Memory-Efficient Multi-Vector Information RetrievalCode1
Context Tuning for Retrieval Augmented Generation—0
PaperQA: Retrieval-Augmented Generative Agent for Scientific Research—0
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering—0
Retrieval-based Video Language Model for Efficient Long Video Question Answering—0
Enhancing Recipe Retrieval with Foundation Models: A Data Augmentation PerspectiveCode1
Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate SystemCode1
Predictive Chemistry Augmented with Text RetrievalCode1
Exploring Radar Data Representations in Autonomous Driving: A Comprehensive ReviewCode2
LifelongMemory: Leveraging LLMs for Answering Queries in Long-form Egocentric VideosCode1
GYM at Qur’an QA 2023 Shared Task: Multi-Task Transfer Learning for Quranic Passage Retrieval and Question Answering with Large Language ModelsCode0
SynthScribe: Deep Multimodal Tools for Synthesizer Sound Retrieval and Exploration—0
STraceBERT: Source Code Retrieval using Semantic Application Traces—0
Lite-Mind: Towards Efficient and Robust Brain Representation NetworkCode1
Learning Genomic Sequence Representations using Graph Neural Networks over De Bruijn GraphsCode0
Boosting legal case retrieval by query content selection with large language modelsCode0
UFineBench: Towards Text-based Person Retrieval with Ultra-fine GranularityCode1
Rethinking E-Commerce Search—0
Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models—0
Uni3DL: Unified Model for 3D and Language Understanding—0
A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense RetrievalCode1
RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!Code2
PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models—0
DRAFT: Dense Retrieval Augmented Few-shot Topic classifier FrameworkCode0
Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic—0
RetriBooru: Leakage-Free Retrieval of Conditions from Reference Images for Subject-Driven Generation—0
FreestyleRet: Retrieving Images from Style-Diversified QueriesCode1
Searching Dense Representations with Inverted Indexes—0
Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models—0
An AI-based solution for the cold start and data sparsity problems in the recommendation systems—0
A Glitch in the Matrix? Locating and Detecting Language Model Grounding with FakepediaCode0
Cross-Modal Adaptive Dual Association for Text-to-Image Person Retrieval—0
How to Configure Good In-Context Sequence for Visual Question AnsweringCode1
Language-only Efficient Training of Zero-shot Composed Image RetrievalCode1
Task tree retrieval from FOON using search algorithms—0
Diffusion Handles: Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D—0
Towards leveraging LLMs for Conditional QA—0
Improve Supervised Representation Learning with Masked Image Modeling—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