4 citations · 6 across the 11 of their papers we have counts for
11 papers
Benchmarking the Generality of Vision-Language-Action Models
Pranav Guruprasad, Sudipta Chowdhury, Harsh Sikka +6
Generalist multimodal agents are expected to unify perception, language, and control - operating robustly across diverse real world domains. However, current evaluation practices r…
An Open-Source Software Toolkit & Benchmark Suite for the Evaluation and Adaptation of Multimodal Action Models
Pranav Guruprasad, Yangyue Wang, Sudipta Chowdhury +2
Recent innovations in multimodal action models represent a promising direction for developing general-purpose agentic systems, combining visual understanding, language comprehensio…
Benchmarking Vision, Language, & Action Models in Procedurally Generated, Open Ended Action Environments
Pranav Guruprasad, Yangyue Wang, Sudipta Chowdhury +2
Vision-language-action (VLA) models represent an important step toward general-purpose robotic systems by integrating visual perception, language understanding, and action executio…
Benchmarking Vision, Language, & Action Models on Robotic Learning Tasks
Pranav Guruprasad, Harshvardhan Sikka, Jaewoo Song +2
Vision-language-action (VLA) models represent a promising direction for developing general-purpose robotic systems, demonstrating the ability to combine visual understanding, langu…
ReFace: Real-time Adversarial Attacks on Face Recognition Systems
Shehzeen Hussain, Todd Huster, Chris Mesterharm +5
Deep neural network based face recognition models have been shown to be vulnerable to adversarial examples. However, many of the past attacks require the adversary to solve an inpu…
WeightScale: Interpreting Weight Change in Neural Networks
Ayush Manish Agrawal, Atharva Tendle, Harshvardhan Sikka +1
Interpreting the learning dynamics of neural networks can provide useful insights into how networks learn and the development of better training and design approaches. We present a…
Investigating Learning in Deep Neural Networks using Layer-Wise Weight Change
Ayush Manish Agrawal, Atharva Tendle, Harshvardhan Sikka +2
Understanding the per-layer learning dynamics of deep neural networks is of significant interest as it may provide insights into how neural networks learn and the potential for bet…
A Genetic Algorithm Based Approach for Satellite Autonomy
Sidhdharth Sikka, Harshvardhan Sikka
Autonomous spacecraft maneuver planning using an evolutionary algorithmic approach is investigated. Simulated spacecraft were placed into four different initial orbits. Each was al…
Benchmarking Differentially Private Residual Networks for Medical Imagery
Sahib Singh, Harshvardhan Sikka, Sasikanth Kotti +1
In this paper we measure the effectiveness of -Differential Privacy (DP) when applied to medical imaging. We compare two robust differential privacy mechanisms: Local-DP and DP-…
A Deeper Look at the Unsupervised Learning of Disentangled Representations in -VAE from the Perspective of Core Object Recognition
Harshvardhan Sikka
The ability to recognize objects despite there being differences in appearance, known as Core Object Recognition, forms a critical part of human perception. While it is understood…
A Closer Look at Disentangling in -VAE
Harshvardhan Sikka, Weishun Zhong, Jun Yin +1
In many data analysis tasks, it is beneficial to learn representations where each dimension is statistically independent and thus disentangled from the others. If data generating f…