POTracker fine-tunes an LLM with POTrackerLoss combining textual and structural similarity, achieving up to 86.47% structural accuracy on 1,000 power outage reports and outperforming baselines by up to 51%.
Data science opportunities of large language models for neuroscience and biomedicine
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
LLMs accelerate research workflows from idea generation to writing but introduce challenges like hallucination, bias, opacity, and ten systemic risks requiring new governance frameworks.
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POTracker: Optimizing Large Language Models for Standard-Compliant Power Outage Report Generation
POTracker fine-tunes an LLM with POTrackerLoss combining textual and structural similarity, achieving up to 86.47% structural accuracy on 1,000 power outage reports and outperforming baselines by up to 51%.