56 citations · 238 across the 48 of their papers we have counts for
57 papers
Uniform-in-Time and Uniform-in-Temperature Particle Approximations of Coulomb MMD Flows
Junho Lee, Promit Ghosal
We study particle approximations of maximum mean discrepancy (MMD) flows with the Coulomb kernel on the torus , , driven by thermal noise of strength .…
Cross-Modal Latent Influence: Patch-Level Training Sample Attribution for Vision-Language Models
Laura Yao, Shixing Yu, Jie Peng +3
Explaining a vision--language model (VLM) prediction requires tracing training-example influence to the multimodal evidence that mediates it, yet existing attribution methods large…
Transporting Randomized Trial Effects to Real-World Populations via Riesz-Calibrated Optimal Transport
Anik Burman, Margaret Gamalo, Promit Ghosal +1
Randomized trials support causal inference, but differences between trial and target populations can limit the transportability of treatment effects to real-world settings. Many ex…
MixCIT: A Kernel Based Local-Polynomial Debiased Test for Conditional Independence on Mixed-Type Data
Mengxiao Gao, Kyra Gan, Promit Ghosal
Conditional independence testing (CIT) is fundamental to modern statistical inference in areas related to causal discovery and variable selection. While marginal independence is re…
Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery
Kingsley Yeon, Xuefeng Liu, Promit Ghosal
Protein-protein interactions (PPIs) govern nearly all cellular processes, yet computational methods for identifying binding partners typically produce ranked predictions without me…
Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces
Shixing Yu, Promit Ghosal, Kyra Gan
A critical step for reliable large language models (LLMs) use in healthcare is to attribute predictions to their training data, akin to a medical case study. This requires token-le…