17 citations · 46 across the 7 of their papers we have counts for
8 papers
To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning
Da JU, Song Jiang, Andrew Cohen +8
Travel planning is a challenging and time-consuming task that aims to find an itinerary which satisfies multiple, interdependent constraints regarding flights, accommodations, attr…
SecAlign: Defending Against Prompt Injection with Preference Optimization
Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar +3
Large language models (LLMs) are becoming increasingly prevalent in modern software systems, interfacing between the user and the Internet to assist with tasks that require advance…
MARS: Multi-radio Architecture with Radio Selection using Decision Trees for emerging mesoscale CPS/IoT applications
Jothi Prasanna Shanmuga Sundaram, Arman Zharmagambetov, Magzhan Gabidolla +2
IoT is rapidly growing from small-scale apps to large-scale apps. Small-scale apps employ short-range radios like Zigbee,BLE while large-scale apps employ long-range radios like Lo…
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo +2
Large Language Models (LLMs) are vulnerable to jailbreaking attacks that lead to generation of inappropriate or harmful content. Manual red-teaming requires a time-consuming search…
GenCO: Generating Diverse Designs with Combinatorial Constraints
Aaron Ferber, Arman Zharmagambetov, Taoan Huang +2
Deep generative models like GAN and VAE have shown impressive results in generating unconstrained objects like images. However, many design settings arising in industrial design, m…
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information
Arman Zharmagambetov, Brandon Amos, Aaron Ferber +3
Recent works in learning-integrated optimization have shown promise in settings where the optimization problem is only partially observed or where general-purpose optimizers perfor…
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
The widespread deployment of deep nets in practical applications has lead to a growing desire to understand how and why such black-box methods perform prediction. Much work has foc…
An Experimental Comparison of Old and New Decision Tree Algorithms
Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán +1
This paper presents a detailed comparison of a recently proposed algorithm for optimizing decision trees, tree alternating optimization (TAO), with other popular, established algor…