Dylan Bouchard

According to our database, Dylan Bouchard authored at least 7 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification.

Dylan Bouchard, Mohit Singh Chauhan, Zeya Ahmad, Ho-Kyeong Ra

CoRR, May, 2026

Is Escalation Worth It? A Decision-Theoretic Characterization of LLM Cascades.

Dylan Bouchard

CoRR, May, 2026

Fine-Grained Uncertainty Quantification for Long-Form Language Model Outputs: A Comparative Study.

Dylan Bouchard, Mohit Singh Chauhan, Viren Bajaj, David Skarbrevik

CoRR, February, 2026

UQLM: A Python Package for Uncertainty Quantification in Large Language Models.

Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, Ho-Kyeong Ra, Viren Bajaj, Zeya Ahmad

J. Mach. Learn. Res., 2026

2025

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases.

Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, Viren Bajaj, Zeya Ahmad

J. Open Source Softw., January, 2025

Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers.

Dylan Bouchard, Mohit Singh Chauhan

Trans. Mach. Learn. Res., 2025

2024

An Actionable Framework for Assessing Bias and Fairness in Large Language Model Use Cases.

Dylan Bouchard

CoRR, 2024