7 papers
You Can't Escape Your Own Activations : Evaluation Awareness and Multi-Agent Monitoring
Aritra Das, Jaee Ponde, Mihir More +1
LLM agents are increasingly deployed in multi-agent systems, where they can collude while keeping their actions benign. Output monitors designed to detect such collusions can be fo…
On the Indistinguishability of Human v/s AI Generated Text
Jaee Ponde, Aritra Das, Mihir More +1
The rapid improvement of LLMs has made distinguishing AI-generated text from human writing a pressing problem. This challenge is further amplified by paraphrasing tools designed to…
Parameterized Complexity of -Lipschitz Constants for Input Convex Neural Networks and -Norm Maximization over Zonotopes
Aritra Das, Vincent Froese, Moritz Grillo +6
Lipschitz constants are a standard way to quantify the sensitivity of neural networks to small input perturbations, but computing them is difficult even for shallow ReLU networks.…
Identifying Intelligent Processes via Online Sequential Testing
Aritra Das, Debayan Gupta
Active sequential hypothesis testing studies how to identify an unknown hypothesis with a given set of sensing actions. We study this in the setting of identifying large language m…
A Rate Separation for Agnostic Direct Sums
Mihir More, Aritra Das, Debayan Gupta
Hanneke, Moran, and Waknine \cite{HannekeMoranWaknine2024} asked how the agnostic PAC learning curve of the direct sum depends on the single-instance learning curve $\epsagn(…
Does Order Matter : Connecting The Law of Robustness to Robust Generalization
Mihir More, Aritra Das, Jaee Ponde +3
Bubeck and Selke (2021) propose the connection between the Law of Robustness and robust generalization error as an open problem. The Law of Robustness states that overparameterizat…
Visual Concept Networks: A Graph-Based Approach to Detecting Anomalous Data in Deep Neural Networks
Debargha Ganguly, Debayan Gupta, Vipin Chaudhary
Deep neural networks (DNNs), while increasingly deployed in many applications, struggle with robustness against anomalous and out-of-distribution (OOD) data. Current OOD benchmarks…