3 citations · 5 across the 4 of their papers we have counts for
7 papers
MJEPA: A Simple and Scalable Joint-Embedding Predictive Architecture for Audio-Visual Learning
Revant Teotia, Adrien Bardes, Michael Rabbat +3
Self-supervised learning from large-scale video data has emerged as a dominant paradigm for visual representation learning. Since audio and visual streams naturally co-occur in vid…
DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models
Revant Teotia, Candace Ross, Karen Ullrich +4
Recent advances in text-to-image (T2I) models have achieved impressive quality and consistency. However, this has come at the cost of representation diversity. While automatic eval…
Fine-Tuning In-House Large Language Models to Infer Differential Diagnosis from Radiology Reports
Luoyao Chen, Revant Teotia, Antonio Verdone +4
Radiology reports summarize key findings and differential diagnoses derived from medical imaging examinations. The extraction of differential diagnoses is crucial for downstream ta…
Affective Faces for Goal-Driven Dyadic Communication
Scott Geng, Revant Teotia, Purva Tendulkar +2
We introduce a video framework for modeling the association between verbal and non-verbal communication during dyadic conversation. Given the input speech of a speaker, our approac…
Doubly Right Object Recognition: A Why Prompt for Visual Rationales
Chengzhi Mao, Revant Teotia, Amrutha Sundar +4
Many visual recognition models are evaluated only on their classification accuracy, a metric for which they obtain strong performance. In this paper, we investigate whether compute…
COFAR: Commonsense and Factual Reasoning in Image Search
Prajwal Gatti, Abhirama Subramanyam Penamakuri, Revant Teotia +3
One characteristic that makes humans superior to modern artificially intelligent models is the ability to interpret images beyond what is visually apparent. Consider the following…
Few-shot Visual Relationship Co-localization
Revant Teotia, Vaibhav Mishra, Mayank Maheshwari +1
In this paper, given a small bag of images, each containing a common but latent predicate, we are interested in localizing visual subject-object pairs connected via the common pred…