CuraView detects sentence-level faithfulness hallucinations in medical discharge summaries via GraphRAG knowledge graphs and multi-agent evidence grading, achieving 0.831 F1 on critical contradictions with a fine-tuned Qwen3-14B model and 50% relative improvement over baselines.
LLMem: Estimating GPU mem- ory usage for fine-tuning pre-trained LLMs
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A systematic evaluation of GPU memory and utilization estimators across analytical, library-based, and ML paradigms identifies key limitations in generalization, integration overhead, and hardware variability for training-aware resource management.
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CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification
CuraView detects sentence-level faithfulness hallucinations in medical discharge summaries via GraphRAG knowledge graphs and multi-agent evidence grading, achieving 0.831 F1 on critical contradictions with a fine-tuned Qwen3-14B model and 50% relative improvement over baselines.
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GPU Memory and Utilization Estimation for Training-Aware Resource Management: Opportunities and Limitations
A systematic evaluation of GPU memory and utilization estimators across analytical, library-based, and ML paradigms identifies key limitations in generalization, integration overhead, and hardware variability for training-aware resource management.