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Retrieval-augmented Generation

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Showing 151–175 of 2196 papers

TitleStatusHype
OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology AlignmentCode2
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuningCode2
CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity KnowledgeCode2
Datrics Text2SQL. A Framework for Natural Language to SQL Query GenerationCode2
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent ControlCode2
CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation GenerationCode2
MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree SearchCode2
EfficientRAG: Efficient Retriever for Multi-Hop Question AnsweringCode2
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to RefuseCode2
MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation SystemsCode2
OntologyRAG: Better and Faster Biomedical Code Mapping with Retrieval-Augmented Generation (RAG) Leveraging Ontology Knowledge Graphs and Large Language ModelsCode2
LitLLM: A Toolkit for Scientific Literature ReviewCode2
CodeRAG-Bench: Can Retrieval Augment Code Generation?Code2
LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and DistillationCode2
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented SearchersCode2
LLM4Ranking: An Easy-to-use Framework of Utilizing Large Language Models for Document RerankingCode2
Learning to Filter Context for Retrieval-Augmented GenerationCode2
LatteReview: A Multi-Agent Framework for Systematic Review Automation Using Large Language ModelsCode2
Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QACode2
Knowledge Graph-Guided Retrieval Augmented GenerationCode2
LARGE: Legal Retrieval Augmented Generation Evaluation ToolCode2
LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal DomainCode2
LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge GraphsCode2
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement LearningCode2
cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax TreeCode2
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