31 citations · 39 across the 8 of their papers we have counts for
4 papers · 1 filter
Can Large Language Models Learn Formal Logic? A Data-Driven Training and Evaluation Framework
Yuan Xia, Akanksha Atrey, Fadoua Khmaissia +1
This paper investigates the logical reasoning capabilities of large language models (LLMs). For a precisely defined yet tractable formulation, we choose the conceptually simple but…
SODA: Protecting Proprietary Information in On-Device Machine Learning Models
Akanksha Atrey, Ritwik Sinha, Saayan Mitra +1
The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and…
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning
Akanksha Atrey, Kaleigh Clary, David Jensen
Saliency maps are frequently used to support explanations of the behavior of deep reinforcement learning (RL) agents. However, a review of how saliency maps are used in practice in…
Measuring and Characterizing Generalization in Deep Reinforcement Learning
Sam Witty, Jun Ki Lee, Emma Tosch +3
Deep reinforcement-learning methods have achieved remarkable performance on challenging control tasks. Observations of the resulting behavior give the impression that the agent has…