10 citations · 13 across the 15 of their papers we have counts for
9 papers · 1 filter
A Shared Encoder Approach to Multimodal Representation Learning
Shuvendu Roy, Franklin Ogidi, Ali Etemad +2
Multimodal representation learning has demonstrated remarkable potential in enabling models to process and integrate diverse data modalities, such as text and images, for improved…
SelfPrompt: Confidence-Aware Semi-Supervised Tuning for Robust Vision-Language Model Adaptation
Shuvendu Roy, Ali Etemad
We present SelfPrompt, a novel prompt-tuning approach for vision-language models (VLMs) in a semi-supervised learning setup. Existing methods for tuning VLMs in semi-supervised set…
Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning
Shuvendu Roy, Yasaman Parhizkar, Franklin Ogidi +5
We perform a comprehensive benchmarking of contrastive frameworks for learning multimodal representations in the medical domain. Through this study, we aim to answer the following…
Consistency-Guided Asynchronous Contrastive Tuning for Few-Shot Class-Incremental Tuning of Foundation Models
Shuvendu Roy, Elham Dolatabadi, Arash Afkanpour +1
We propose Consistency-guided Asynchronous Contrastive Tuning (CoACT), a novel method for continuously tuning foundation models to learn new classes in few-shot settings. CoACT con…
A Bag of Tricks for Few-Shot Class-Incremental Learning
Shuvendu Roy, Chunjong Park, Aldi Fahrezi +1
We present a bag of tricks framework for few-shot class-incremental learning (FSCIL), which is a challenging form of continual learning that involves continuous adaptation to new t…
Contrastive Learning of View-Invariant Representations for Facial Expressions Recognition
Shuvendu Roy, Ali Etemad
Although there has been much progress in the area of facial expression recognition (FER), most existing methods suffer when presented with images that have been captured from viewi…