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Retrieval-augmented Generation

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Showing 1051–1100 of 2196 papers

TitleStatusHype
QuIM-RAG: Advancing Retrieval-Augmented Generation with Inverted Question Matching for Enhanced QA Performance—0
QuOTE: Question-Oriented Text Embeddings—0
Qwen2.5-32B: Leveraging Self-Consistent Tool-Integrated Reasoning for Bengali Mathematical Olympiad Problem Solving—0
R^3AG: First Workshop on Refined and Reliable Retrieval Augmented Generation—0
R^3Mem: Bridging Memory Retention and Retrieval via Reversible Compression—0
RAAD-LLM: Adaptive Anomaly Detection Using LLMs and RAG Integration—0
RAC3: Retrieval-Augmented Corner Case Comprehension for Autonomous Driving with Vision-Language Models—0
RAD: Retrieval-Augmented Decision-Making of Meta-Actions with Vision-Language Models in Autonomous Driving—0
RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenance—0
Rag and Roll: An End-to-End Evaluation of Indirect Prompt Manipulations in LLM-based Application Frameworks—0
RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models—0
RAG-based Crowdsourcing Task Decomposition via Masked Contrastive Learning with Prompts—0
RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models—0
RAG based Question-Answering for Contextual Response Prediction System—0
RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems—0
RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation—0
RAG-Check: Evaluating Multimodal Retrieval Augmented Generation Performance—0
RAGDiffusion: Faithful Cloth Generation via External Knowledge Assimilation—0
RAG Does Not Work for Enterprises—0
Natural Language Interaction with a Household Electricity Knowledge-based Digital Twin—0
RAG-Enhanced Collaborative LLM Agents for Drug Discovery—0
RAG+: Enhancing Retrieval-Augmented Generation with Application-Aware Reasoning—0
RAGent: Retrieval-based Access Control Policy Generation—0
RAG for Effective Supply Chain Security Questionnaire Automation—0
RAG-Fusion: a New Take on Retrieval-Augmented Generation—0
RAGged Edges: The Double-Edged Sword of Retrieval-Augmented Chatbots—0
RAG-Gym: Optimizing Reasoning and Search Agents with Process Supervision—0
RAG-KG-IL: A Multi-Agent Hybrid Framework for Reducing Hallucinations and Enhancing LLM Reasoning through RAG and Incremental Knowledge Graph Learning Integration—0
RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models—0
RAG-MCP: Mitigating Prompt Bloat in LLM Tool Selection via Retrieval-Augmented Generation—0
RAGONITE: Iterative Retrieval on Induced Databases and Verbalized RDF for Conversational QA over KGs with RAG—0
RAG-Optimized Tibetan Tourism LLMs: Enhancing Accuracy and Personalization—0
RAG-Reward: Optimizing RAG with Reward Modeling and RLHF—0
RAG-RL: Advancing Retrieval-Augmented Generation via RL and Curriculum Learning—0
RAGServe: Fast Quality-Aware RAG Systems with Configuration Adaptation—0
RAGSys: Item-Cold-Start Recommender as RAG System—0
RAGtifier: Evaluating RAG Generation Approaches of State-of-the-Art RAG Systems for the SIGIR LiveRAG Competition—0
RAG-Verus: Repository-Level Program Verification with LLMs using Retrieval Augmented Generation—0
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture—0
RAG vs. GraphRAG: A Systematic Evaluation and Key Insights—0
Examining Long-Context Large Language Models for Environmental Review Document Comprehension—0
RAG Without the Lag: Interactive Debugging for Retrieval-Augmented Generation Pipelines—0
RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models—0
RAGXplain: From Explainable Evaluation to Actionable Guidance of RAG Pipelines—0
RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning—0
Raiders of the Lost Dependency: Fixing Dependency Conflicts in Python using LLMs—0
RAMO: Retrieval-Augmented Generation for Enhancing MOOCs Recommendations—0
Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains—0
RankLLM: A Python Package for Reranking with LLMs—0
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs—0
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