collaborators

5 papers

cs.LG2026

FUSE: Feature-Wise Unified Specialization with Cross-Column Exchange for Mixed-Type Tabular Flow Matching

Suman Cha, Seongchan Lee, Dohyun Ko +1

Generating mixed-type tabular data requires jointly modeling diverse feature distributions and their complex cross-column dependencies. Variational flow matching handles distinct e…

math.PR2026

A Sharper Hoeffding Bound for Weighted Sums of Exchangeable Random Variables

Seongchan Lee, Ilmun Kim

We prove a Hoeffding-type moment generating function bound for weighted sums of bounded exchangeable random variables centered by their finite-population average. The bound improve…

stat.CO2026

More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests

Suman Cha, Seongchan Lee, Antonin Schrab +1

Monte Carlo permutation tests are a cornerstone of valid, model-free statistical inference. A widely held practical intuition is that increasing the number of sampled permutations…

stat.ML2026

General Frameworks for Conditional Two-Sample Testing

Seongchan Lee, Suman Cha, Ilmun Kim

We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This pr…

cs.LG2026

Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses

Kangjun Noh, Seongchan Lee, Ilmun Kim +1

Ensuring factuality is essential for the safe use of Large Language Models (LLMs) in high-stakes domains such as medicine and law. Conformal inference provides distribution-free gu…