15 papers
Beyond "AI Helps Humans": Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic Era
Hamed Khosravi, Xiaoming Huo
Wherever a coding agent works under engineer supervision, or a clinical model assists a radiologist, the deployment question is whether to keep the human-AI workflow or replace it…
Which LLM for Which Work? Budgeted Model Allocation under Uncertain Evaluation
Hamed Khosravi, Xiaoming Huo
A company with a fixed artificial intelligence (AI) budget must decide which large language model (LLM) handles each recurring workload. What it lacks is the quality table, how wel…
The Noise Premium in Adversarial Training for Kernel Regression
Yiling Xie, Xiaoming Huo
Adversarial training can improve the robustness of predictive models to bounded perturbations, often at the cost of statistical efficiency. We study this trade-off in kernel regres…
A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes
Yijin Ni, Xiaoming Huo
Fair representation learning with a continuous sensitive attribute requires a representation that is statistically independent of . Existing criteria, including generali…
A Polyak-Ruppert Central Limit Theorem for SA-Adam with Momentum and Non-Convergent Adaptive Preconditioning
Sunyoung An, Xiaoming Huo
Adaptive optimizers combining preconditioning, momentum, and weight decay (Adam and AdamW) are, under Polyak-Ruppert averaging, candidate engines for one-pass inference. Does the a…
Matching Rates and Optimal Allocation for Federated Probe-Logit Distillation under Heterogeneous Bandwidth Budgets
Prasanjit Dubey, Xiaoming Huo
In federated language modeling, nodes each hold samples but cannot pool data or exchange full-precision gradients or weights. We study the minimax rate at which a condition…