3 citations · 5 across the 5 of their papers we have counts for
7 papers
The Geometry of Robustness: Optimizing Loss Landscape Curvature and Feature Manifold Alignment for Robust Finetuning of Vision-Language Models
Shivang Chopra, Shaunak Halbe, Chengyue Huang +2
Fine-tuning approaches for Vision-Language Models (VLMs) face a critical three-way trade-off between In-Distribution (ID) accuracy, Out-of-Distribution (OOD) generalization, and ad…
VeRVE: Versatile Retrieval for Videos via Unified Embeddings
Shaunak Halbe, Bhagyashree Puranik, Jayakrishnan Unnikrishnan +3
Modern video retrieval systems are expected to handle diverse tasks ranging from corpus-level retrieval, fine-grained moment localization to flexible multimodal querying. Specializ…
Grounding Descriptions in Images informs Zero-Shot Visual Recognition
Shaunak Halbe, Junjiao Tian, K J Joseph +4
Vision-language models (VLMs) like CLIP have been cherished for their ability to perform zero-shot visual recognition on open-vocabulary concepts. This is achieved by selecting the…
Adaptive Memory Replay for Continual Learning
James Seale Smith, Lazar Valkov, Shaunak Halbe +4
Foundation Models (FMs) have become the hallmark of modern AI, however, these models are trained on massive data, leading to financially expensive training. Updating FMs as new dat…
Continual Adaptation of Vision Transformers for Federated Learning
Shaunak Halbe, James Seale Smith, Junjiao Tian +1
In this paper, we focus on the important yet understudied problem of Continual Federated Learning (CFL), where a server communicates with a set of clients to incrementally learn ne…
Robustness through Data Augmentation Loss Consistency
Tianjian Huang, Shaunak Halbe, Chinnadhurai Sankar +5
While deep learning through empirical risk minimization (ERM) has succeeded at achieving human-level performance at a variety of complex tasks, ERM is not robust to distribution sh…
Exploring Weaknesses of VQA Models through Attribution Driven Insights
Shaunak Halbe
Deep Neural Networks have been successfully used for the task of Visual Question Answering for the past few years owing to the availability of relevant large scale datasets. Howeve…