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Retrieval-augmented Generation

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TitleStatusHype
Benchmarking Large Language Models in Retrieval-Augmented GenerationCode2
Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph ConstructionCode2
DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented GenerationCode2
Evaluation of Retrieval-Augmented Generation: A SurveyCode2
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to RefuseCode2
Evaluating RAG-Fusion with RAGElo: an Automated Elo-based FrameworkCode2
Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented GenerationCode2
Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge EnhancementCode2
Huatuo-26M, a Large-scale Chinese Medical QA DatasetCode2
RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within GenerationCode2
A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question AnsweringCode1
Long-Context Inference with Retrieval-Augmented Speculative DecodingCode1
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation ModelsCode1
Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented GenerationCode1
Long Context vs. RAG for LLMs: An Evaluation and RevisitsCode1
Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-BasesCode1
Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial TrainingCode1
End-to-End Learning of Flowchart Grounded Task-Oriented DialogsCode1
ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAGCode1
LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and RegularizationCode1
Emotional RAG: Enhancing Role-Playing Agents through Emotional RetrievalCode1
Enhancing Retrieval and Managing Retrieval: A Four-Module Synergy for Improved Quality and Efficiency in RAG SystemsCode1
LLMs Know What They Need: Leveraging a Missing Information Guided Framework to Empower Retrieval-Augmented GenerationCode1
Logic-RAG: Augmenting Large Multimodal Models with Visual-Spatial Knowledge for Road Scene UnderstandingCode1
MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAGCode1
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