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Medical Question Answering

Papers

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Showing 1–25 of 139 papers

TitleStatusHype
Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up QuestionsCode4
Benchmarking Retrieval-Augmented Generation for MedicineCode4
Huatuo-26M, a Large-scale Chinese Medical QA DatasetCode2
Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language ModelsCode2
GreaseLM: Graph REASoning Enhanced Language Models for Question AnsweringCode2
Med-MoE: Mixture of Domain-Specific Experts for Lightweight Medical Vision-Language ModelsCode2
MedAgentsBench: Benchmarking Thinking Models and Agent Frameworks for Complex Medical ReasoningCode2
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical ReasoningCode2
AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction SimulatorCode2
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical DomainsCode2
PMC-LLaMA: Towards Building Open-source Language Models for MedicineCode2
MedLM: Exploring Language Models for Medical Question Answering SystemsCode1
LingYi: Medical Conversational Question Answering System based on Multi-modal Knowledge GraphsCode1
Mitigating Unintended Memorization with LoRA in Federated Learning for LLMsCode1
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global InferenceCode1
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language ModelsCode1
Large language model validity via enhanced conformal prediction methodsCode1
Kformer: Knowledge Injection in Transformer Feed-Forward LayersCode1
KnowTuning: Knowledge-aware Fine-tuning for Large Language ModelsCode1
Integrating UMLS Knowledge into Large Language Models for Medical Question AnsweringCode1
A Gradually Soft Multi-Task and Data-Augmented Approach to Medical Question UnderstandingCode1
JMedLoRA:Medical Domain Adaptation on Japanese Large Language Models using Instruction-tuningCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
FiTs: Fine-grained Two-stage Training for Knowledge-aware Question AnsweringCode1
Benchmarking large language models for biomedical natural language processing applications and recommendationsCode1
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