181 citations · 184 across the 10 of their papers we have counts for
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InPhyRe Discovers: Large Multimodal Models Struggle in Inductive Physical Reasoning
Gautam Sreekumar, Vishnu Naresh Boddeti
Large multimodal models (LMMs) encode physical laws observed during training, such as momentum conservation, as parametric knowledge. It allows LMMs to answer physical reasoning qu…
Incorporating Interventional Independence Improves Robustness against Interventional Distribution Shift
Gautam Sreekumar, Vishnu Naresh Boddeti
We study the problem of learning robust discriminative representations of causally related latent variables given the underlying causal graph and a training set comprising passivel…
CoInD: Enabling Logical Compositions in Diffusion Models
Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti
How can we learn generative models to sample data with arbitrary logical compositions of statistically independent attributes? The prevailing solution is to sample from distributio…
Compositional World Knowledge leads to High Utility Synthetic data
Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti
Machine learning systems struggle with robustness, under subpopulation shifts. This problem becomes especially pronounced in scenarios where only a subset of attribute combinations…
OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes
Sepehr Dehdashtian, Gautam Sreekumar, Vishnu Naresh Boddeti
Images generated by text-to-image (T2I) models often exhibit visual biases and stereotypes of concepts such as culture and profession. Existing quantitative measures of stereotypes…