63 citations · 81 across the 42 of their papers we have counts for
8 papers · 1 filter
Controller-Agnostic Runtime Safety Certificates for Tool-Using AI Agents via Data-Driven Robust Reachability
Ali Baheri, Peng Wei
Software agents built on large language models act by issuing tool calls, some of which cannot be undone. To control theory the model is an opaque feedback controller, replaced eve…
Flow-Corrected Thompson Sampling for Non-Stationary Contextual Bandits
Ali Baheri, AmirHossein Naghdi
We study non-stationary linear contextual bandits where the reward model drifts over time, rendering classical contextual bandit algorithms brittle because historical data becomes…
Wasserstein Stability of Contracting Flows: Effective Rates, Euler Self-Correction, and Noise Tightening
Ali Baheri
Contraction theory guaranties exponential convergence between trajectories of a stable nonlinear system. When initial conditions are uncertain and represented as probability distri…
Can We Formally Verify Neural PDE Surrogates? SMT Compilation of Small Fourier Neural Operators
Ali Baheri, Ignacio Laguna Peralta
Fourier Neural Operators (FNOs) can greatly accelerate PDE simulation, but they are often used without formal guarantees that they preserve basic physical structure. We show that,…
Where Does Reasoning Break? Step-Level Hallucination Detection via Hidden-State Transport Geometry
Tyler Alvarez, Ali Baheri
Large language models hallucinate during multi-step reasoning, but most existing detectors operate at the trace level: they assign one confidence score to a full output, fail to lo…
Geometry-Aware Uncertainty Quantification via Conformal Prediction on Manifolds
Marzieh Amiri Shahbazi, Ali Baheri
Conformal prediction gives finite-sample coverage guarantees for regression, but most standard constructions are designed for Euclidean output spaces. When the response lies on a R…
Adaptive Conformal Prediction via Bayesian Uncertainty Weighting for Hierarchical Healthcare Data
Marzieh Amiri Shahbazi, Ali Baheri, Nasibeh Azadeh-Fard
Clinical decision-making demands uncertainty quantification that provides both distribution-free coverage guarantees and risk-adaptive precision, requirements that existing methods…
Can Optimal Transport Improve Federated Inverse Reinforcement Learning?
David Millard, Ali Baheri
In robotics and multi-agent systems, fleets of autonomous agents often operate in subtly different environments while pursuing a common high-level objective. Directly pooling their…