1 citations · 2 across the 14 of their papers we have counts for
4 papers · 1 filter
ViLBias: Detecting and Reasoning about Bias in Multimodal Content
Shaina Raza, Caesar Saleh, Azib Farooq +11
Detecting bias in multimodal news requires models that reason over text--image pairs, not just classify text. In response, we present ViLBias, a VQA-style benchmark and framework f…
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of Augmentation
Mohammad Akhavan Anvari, Rojina Kashefi, Vahid Reza Khazaie +2
Anomaly detection involves identifying instances within a dataset that deviate from the norm and occur infrequently. Current benchmarks tend to favor methods biased towards low div…
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…
Can Generative Models Improve Self-Supervised Representation Learning?
Sana Ayromlou, Vahid Reza Khazaie, Fereshteh Forghani +1
The rapid advancement in self-supervised representation learning has highlighted its potential to leverage unlabeled data for learning rich visual representations. However, the exi…