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Retrieval-augmented Generation

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Showing 601–625 of 2196 papers

TitleStatusHype
MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning—0
DGRAG: Distributed Graph-based Retrieval-Augmented Generation in Edge-Cloud Systems—0
Project Riley: Multimodal Multi-Agent LLM Collaboration with Emotional Reasoning and Voting—0
HomeBench: Evaluating LLMs in Smart Homes with Valid and Invalid Instructions Across Single and Multiple DevicesCode0
Retrieval-Augmented Generation for Service Discovery: Chunking Strategies and Benchmarking—0
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval Augmented Generation Across Learning Style—0
Hypercube-RAG: Hypercube-Based Retrieval-Augmented Generation for In-domain Scientific Question-AnsweringCode0
RankLLM: A Python Package for Reranking with LLMs—0
Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer AssistanceCode0
Federated Retrieval-Augmented Generation: A Systematic Mapping Study—0
Towards Emotionally Consistent Text-Based Speech Editing: Introducing EmoCorrector and The ECD-TSE DatasetCode0
BRIT: Bidirectional Retrieval over Unified Image-Text Graph—0
Retrieval Augmented Decision-Making: A Requirements-Driven, Multi-Criteria Framework for Structured Decision Support—0
LLMs for Supply Chain Management—0
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation—0
The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems—0
Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMsCode0
Retrieval Augmented Generation-based Large Language Models for Bridging Transportation Cybersecurity Legal Knowledge Gaps—0
Hard Negative Mining for Domain-Specific Retrieval in Enterprise Systems—0
FinRAGBench-V: A Benchmark for Multimodal RAG with Visual Citation in the Financial Domain—0
Tools in the Loop: Quantifying Uncertainty of LLM Question Answering Systems That Use Tools—0
Continually Self-Improving Language Models for Bariatric Surgery Question--Answering—0
HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation—0
Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature SummarizationCode0
Chain-of-Thought Poisoning Attacks against R1-based Retrieval-Augmented Generation Systems—0
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