7 citations · 9 across the 4 of their papers we have counts for
4 papers
Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks
Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu +2
We investigate the success conditions for compositional generalization of CLIP models on real-world data through performance prediction. Prior work shows that CLIP requires exponen…
No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance
Vishaal Udandarao, Ameya Prabhu, Adhiraj Ghosh +5
Web-crawled pretraining datasets underlie the impressive "zero-shot" evaluation performance of multimodal models, such as CLIP for classification/retrieval and Stable-Diffusion for…
Gujarati-English Code-Switching Speech Recognition using ensemble prediction of spoken language
Yash Sharma, Basil Abraham, Preethi Jyothi
An important and difficult task in code-switched speech recognition is to recognize the language, as lots of words in two languages can sound similar, especially in some accents. W…
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies
Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma +4
This work introduces a novel principle for disentanglement we call mechanism sparsity regularization, which applies when the latent factors of interest depend sparsely on observed…