4 papers
What Can Low Resource Languages Learn From Each Other?
Achyuth P, Kahaan Shah, Chetan Arora
Despite the rapid advancement of Vision-Language Models (VLMs), their linguistic reach remains largely confined to high-resource languages, leaving the majority of the world's 7,00…
Enhancing Deep Neural Network Reliability with Refinement and Calibration
Ramya Hebbalaguppe, Ajay Shastry, Soumya Suvra Ghosal +1
Although deep neural networks (DNNs) achieve high predictive accuracy, their confidence estimates are often unreliable, potentially compromising user trust in their decisions. This…
CLIP-Inspector: Model-Level Backdoor Detection for Prompt-Tuned CLIP via OOD Trigger Inversion
Akshit Jindal, Saket Anand, Chetan Arora +1
Organisations with limited data and computational resources increasingly outsource model training to Machine Learning as a Service (MLaaS) providers, who adapt vision-language mode…
Prompting without Panic: Attribute-aware, Zero-shot, Test-Time Calibration
Ramya Hebbalaguppe, Tamoghno Kandar, Abhinav Nagpal +1
Vision-language models (VLM) have demonstrated impressive performance in image recognition by leveraging self-supervised training on large datasets. Their performance can be furthe…