4 papers
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…
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…
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…
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…