4 citations · 5 across the 4 of their papers we have counts for
4 papers
Label Poisoning is All You Need
Rishi D. Jha, Jonathan Hayase, Sewoong Oh
In a backdoor attack, an adversary injects corrupted data into a model's training dataset in order to gain control over its predictions on images with a specific attacker-defined t…
Adversarial Illusions in Multi-Modal Embeddings
Tingwei Zhang, Rishi Jha, Eugene Bagdasaryan +1
Multi-modal embeddings encode texts, images, thermal images, sounds, and videos into a single embedding space, aligning representations across different modalities (e.g., associate…
Hyper-Universal Policy Approximation: Learning to Generate Actions from a Single Image using Hypernets
Dimitrios C. Gklezakos, Rishi Jha, Rajesh P. N. Rao
Inspired by Gibson's notion of object affordances in human vision, we ask the question: how can an agent learn to predict an entire action policy for a novel object or environment…
On Geodesic Distances and Contextual Embedding Compression for Text Classification
Rishi Jha, Kai Mihata
In some memory-constrained settings like IoT devices and over-the-network data pipelines, it can be advantageous to have smaller contextual embeddings. We investigate the efficacy…