3 papers
cs.AI2026
Fine-Tuning Fixes Mode Collapse and Over-Dispersion in LLMs
Kirill Skobelev, Eric Fithian, X. Y. Han
Recent work by Doshi and Hauser (2024), Bisbee et al. (2024), and Xie et al. (2026) raises concerns that outputs from large language models (LLMs) tend to be under-diverse: they re…
cs.AI2026
A Comparative Study in Surgical AI: Potential and Limitations of Data, Compute, and Scaling
Kirill Skobelev, Eric Fithian, Yegor Baranovski +9
Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but surgical benchmarks in particular are of…
cs.IR2025
DELM: a Python toolkit for Data Extraction with Language Models
Eric Fithian, Kirill Skobelev
Large Language Models (LLMs) have become powerful tools for annotating unstructured data. However, most existing workflows rely on ad hoc scripts, making reproducibility, robustnes…