collaborators

5 papers

cs.DL2026

Allocate Marginal Reviews to Borderline Papers Using LLM Comparative Ranking

Elliot L. Epstein, Rajat Dwaraknath, John Winnicki +1

This paper argues that large ML conferences should allocate marginal review capacity primarily to papers near the acceptance boundary, rather than spreading extra reviews via rando…

math.OC2026

Differentiable Integer Linear Programming is not Differentiable & it's not a mere technical problem

Thanawat Sornwanee

We show how the differentiability method employed in the paper ``Differentiable Integer Linear Programming'', Geng, et al., 2025 as shown in its theorem 5 is incorrect. Moreover, t…

stat.ME2025

LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval

Elliot L. Epstein, John Winnicki, Thanawat Sornwanee +1

Large language models (LLMs) excel at numerical estimation but struggle to correctly quantify uncertainty. We study how well LLMs construct confidence intervals around their own an…

econ.TH2025

1-Dimensional Normal Competitive Market Equilibrium

Thanawat Sornwanee

We introduce a new microeconomics foundation of a specific type of competitive market equilibrium that can be used to study several markets with information asymmetry such as commo…

cs.LG2025

SD-KDE: Score-Debiased Kernel Density Estimation

Elliot L. Epstein, Rajat Dwaraknath, Thanawat Sornwanee +2

We propose a novel method for density estimation that leverages an estimated score function to debias kernel density estimation (SD-KDE). In our approach, each data point is adjust…