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Retrieval-augmented Generation

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Showing 126–150 of 2196 papers

TitleStatusHype
Evaluating RAG-Fusion with RAGElo: an Automated Elo-based FrameworkCode2
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language ModelsCode2
QAEncoder: Towards Aligned Representation Learning in Question Answering SystemCode2
MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation SystemsCode2
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language ModelsCode2
Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-LearningCode2
Enhancing Retrieval-Augmented Generation: A Study of Best PracticesCode2
EfficientRAG: Efficient Retriever for Multi-Hop Question AnsweringCode2
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to RefuseCode2
MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree SearchCode2
LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge GraphsCode2
cAST: Enhancing Code Retrieval-Augmented Generation with Structural Chunking via Abstract Syntax TreeCode2
LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question AnsweringCode2
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"Code2
MetaOpenFOAM: an LLM-based multi-agent framework for CFDCode2
LLM4Ranking: An Easy-to-use Framework of Utilizing Large Language Models for Document RerankingCode2
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor SearchCode2
Multi-Reranker: Maximizing performance of retrieval-augmented generation in the FinanceRAG challengeCode2
Qilin: A Multimodal Information Retrieval Dataset with APP-level User SessionsCode2
LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal DomainCode2
Biomedical knowledge graph-optimized prompt generation for large language modelsCode2
Language Model Powered Digital Biology with BRADCode2
Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based RetrieversCode2
LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented SearchersCode2
Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial ApplicationsCode2
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