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A Physics Prediction Task to Evaluate LLM Reasoning
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A Physics Prediction Task to Evaluate LLM Reasoning

Caleb Bradshaw

A novel physics prediction benchmark for large language models

LLMsEvaluationPhysicsCalibrationMachine Learning
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Publications

LLM Generated Distribution-Based Prediction of US Electoral Results, Part I

LLM Generated Distribution-Based Prediction of US Electoral Results, Part I

Caleb Bradshaw, Caelen Miller, Sean Warnick

arXiv

This paper introduces Distribution-Based Prediction, a method for interpreting LLM output probabilities as predictive distributions. Applied to US elections, it enables analysis of model bias, prompt noise, and algorithmic fidelity.

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Taking the Derivative of a Story: A Novel Approach to Fiction Scene Segmentation

Taking the Derivative of a Story: A Novel Approach to Fiction Scene Segmentation

Michael DeBuse, Caelen Miller, Caleb Bradshaw, Abel Palmer, Sean Warnick

TACL (under review)

This paper introduces a new method for scene segmentation in fiction by calculating a 'derivative' over sentence embeddings, using local minima as candidates for scene transitions.

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