Adversarial Evasion on LLMs

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This paper focuses on source-free domain adaptation for object detection in computer vision. This task is challenging and of great practical interest, due to the cost of obtaining annotated data sets for every new domain. Recent research has proposed vario ...

This paper presents STEEL-3dPointClouds, a dataset of deformed steel beam-columns obtained using high-fidelity physics-based numerical simulations. These simulations trace the inelastic deformations of hot-rolled wide-flange steel beam-columns under differ ...

In this work, we focus on the design of optimal controllers that must comply with an information structure. State-of-the-art approaches do so based on the H2 or H∞ norm to minimize the expected or worst-case cost in the presence of stochastic or adversaria ...

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of anim ...

Adversarial Evasion on LLMs

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Simplifying Source-Free Domain Adaptation for Object Detection: Effective Self-training Strategies and Performance Insights

STEEL-3dPointClouds: dataset supporting quantification of residual life and reusability of steel beam-columns

Closing the Gap to Quadratic Invariance: A Regret Minimization Approach to Optimal Distributed Control

AmadeusGPT: a natural language interface for interactive animal behavioral analysis