NodeSynth creates evidence-based synthetic queries via a taxonomy generator to evaluate LLMs, revealing up to 5x higher failure rates than human benchmarks and gaps in guard models.
Aloe: A family of fine-tuned open healthcare llms
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Releases open medical LVLMs trained on a quality-filtered multimodal dataset, introduces CareQA-Vision benchmark from exams, reports performance gains over baselines, and flags adversarial vulnerabilities.
FLAME applies fine-grained list-wise alignment and Group Relative Policy Optimization to large language models for generating safe medication recommendations by sequentially adding or removing drugs.
citing papers explorer
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NodeSynth: Socially Aligned Synthetic Data for AI Evaluation
NodeSynth creates evidence-based synthetic queries via a taxonomy generator to evaluate LLMs, revealing up to 5x higher failure rates than human benchmarks and gaps in guard models.
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Aloe-Vision: Robust Vision-Language Models for Healthcare
Releases open medical LVLMs trained on a quality-filtered multimodal dataset, introduces CareQA-Vision benchmark from exams, reports performance gains over baselines, and flags adversarial vulnerabilities.
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Fine-grained List-wise Alignment for Generative Medication Recommendation
FLAME applies fine-grained list-wise alignment and Group Relative Policy Optimization to large language models for generating safe medication recommendations by sequentially adding or removing drugs.