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Retrieval-augmented Generation

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TitleStatusHype
DH-RAG: A Dynamic Historical Context-Powered Retrieval-Augmented Generation Method for Multi-Turn Dialogue—0
Retrieval-augmented systems can be dangerous medical communicators—0
HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation—0
PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational PathsCode3
Towards an automated workflow in materials science for combining multi-modal simulative and experimental information using data mining and large language models—0
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation—0
Language Models are Few-Shot Graders—0
RAPID: Retrieval Augmented Training of Differentially Private Diffusion ModelsCode0
SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?—0
REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark—0
SmartLLM: Smart Contract Auditing using Custom Generative AI—0
Cognitive-Aligned Document Selection for Retrieval-augmented Generation—0
Revisiting Robust RAG: Do We Still Need Complex Robust Training in the Era of Powerful LLMs?—0
FineFilter: A Fine-grained Noise Filtering Mechanism for Retrieval-Augmented Large Language Models—0
Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics—0
Does RAG Really Perform Bad For Long-Context Processing?—0
FaMTEB: Massive Text Embedding Benchmark in Persian Language—0
Fast or Better? Balancing Accuracy and Cost in Retrieval-Augmented Generation with Flexible User ControlCode0
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights—0
Multi-Modal Retrieval Augmentation for Open-Ended and Knowledge-Intensive Video Question Answering—0
REVERSUM: A Multi-staged Retrieval-Augmented Generation Method to Enhance Wikipedia Tail Biographies through Personal NarrativesCode0
IterQR: An Iterative Framework for LLM-based Query Rewrite in e-Commercial Search System—0
Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs—0
Investigating Language Preference of Multilingual RAG Systems—0
RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM GenerationCode2
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