collaborators

5 papers

cs.CV2026

PatchPoison: Poisoning Multi-View Datasets to Degrade 3D Reconstruction

Prajas Wadekar, Venkata Sai Pranav Bachina, Kunal Bhosikar +2

3D Gaussian Splatting (3DGS) has recently enabled highly photorealistic 3D reconstruction from casually captured multi-view images. However, this accessibility raises a privacy con…

cs.LG2025

LoReTTA: A Low Resource Framework To Poison Continuous Time Dynamic Graphs

Himanshu Pal, Venkata Sai Pranav Bachina, Ankit Gangwal +1

Temporal Graph Neural Networks (TGNNs) are increasingly used in high-stakes domains, such as financial forecasting, recommendation systems, and fraud detection. However, their susc…

cs.LG2025

Merge Now, Regret Later: The Hidden Cost of Model Merging Is Adversarial Transferability

Mauro Conti, Ankit Gangwal, Aaryan Ajay Sharma

Model Merging (MM) has proven to be an effective alternative to multi-task learning, where several fine-tuned models are merged, without access to the tasks' training data, into on…

cs.CR2025

KeTS: Kernel-based Trust Segmentation against Model Poisoning Attacks

Ankit Gangwal, Mauro Conti, Tommaso Pauselli

Federated Learning (FL) enables multiple users to collaboratively train a global model in a distributed manner without revealing their personal data. However, FL remains vulnerable…

cs.CR2025

GENIE: Watermarking Graph Neural Networks for Link Prediction

Venkata Sai Pranav Bachina, Ankit Gangwal, Aaryan Ajay Sharma +1

Graph Neural Networks (GNNs) have become invaluable intellectual property in graph-based machine learning. However, their vulnerability to model stealing attacks when deployed with…