activity
20242026
collaborators

6 papers

eess.SY2026

HyperCertificates: Verification of Discrete-time Dynamical Systems against HyperLTL Specifications

Vishnu Murali, Amin Falah, Ashutosh Trivedi +1

We introduce a functional inductive framework to verify discrete-time dynamical systems against hyperproperties specified as Hyperlinear temporal logic formulae via a notion of Hyp…

cs.CL2026

Monotonicity as an Architectural Bias for Robust Language Models

Patrick Cooper, Alireza Nadali, Ashutosh Trivedi +1

Large language models (LLMs) are known to exhibit brittle behavior under adversarial prompts and jailbreak attacks, even after extensive alignment and fine-tuning. This fragility r…

eess.SY2026

Monotone Neural Barrier Certificates

Saber Jafarpour, Alireza Nadali, Ashutosh Trivedi +1

This report presents a neurosymbolic framework for safety verification and control synthesis in high-dimensional monotone dynamical systems without relying on explicit models or co…

cs.FL2026

Co-Buchi Barrier Certificates for Discrete-time Dynamical Systems

Vishnu Murali, Ashutosh Trivedi, Majid Zamani

Barrier certificates provide functional overapproximations for the reachable set of dynamical systems and provide inductive guarantees on the safe evolution of the system. In autom…

cs.LG2025

Physics-Informed Reward Machines

Daniel Ajeleye, Ashutosh Trivedi, Majid Zamani

Reward machines (RMs) provide a structured way to specify non-Markovian rewards in reinforcement learning (RL), thereby improving both expressiveness and programmability. Viewed mo…

eess.SY2024

Transfer Learning for Control Systems via Neural Simulation Relations

Alireza Nadali, Bingzhuo Zhong, Ashutosh Trivedi +1

Transfer learning is an umbrella term for machine learning approaches that leverage knowledge gained from solving one problem (the source domain) to improve speed, efficiency, and…