#perturbation-analysis News & Analysis

2 articles tagged with #perturbation-analysis. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Mar 56/10

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Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations

Research reveals that Large Language Models show varying vulnerabilities to different types of Chain-of-Thought reasoning perturbations, with math errors causing 50-60% accuracy loss in small models while unit conversion issues remain challenging even for the largest models. The study tested 13 models across parameter ranges from 3B to 1.5T parameters, finding that scaling provides protection against some perturbations but limited defense against dimensional reasoning tasks.

AINeutralarXiv – CS AI · Jun 26/10

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Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning

Researchers demonstrate that large language models fail to accurately predict gene expression changes in cellular perturbation experiments despite producing biologically plausible explanations. They introduce CORE, a contrastive learning method that significantly improves prediction accuracy by organizing evidence from related perturbations rather than evaluating them in isolation.