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20202026
most citedRobustness through Data Augmentation Loss Consistency

3 citations · 5 across the 5 of their papers we have counts for

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cs.CV2026

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…

cs.CV2026

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…

cs.CV2024

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…

cs.CV2023★ 1 cited

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…

cs.CV2020

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…