Bhanu Tokas — accepted AI-conference papers

2026

MOMO: Mars Orbital MOdel Foundation Model for Mars Orbital Applications

Mirali Purohit, Bimal Gajera, Irish Mehta, Bhanu Tokas, Jacob Adler, Steven Lu +5

CVPR 2026

We introduce MOMO, the first multi-sensor foundation model for Mars remote sensing. MOMO uses model merge to integrate representations learned independently from three key Martian sensors (HiRISE, CTX, and THEMIS), spanning resolutions from 0.25 m/pixel to 100 m/pixel. Central to our method is our n

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2025

DPA: A one-stop metric to measure bias amplification in classification datasets

Bhanu Tokas, Rahul Nair, Hannah Kerner

NeurIPS 2025poster

Most ML datasets today contain biases. When we train models on these datasets, they often not only learn these biases but can worsen them --- a phenomenon known as bias amplification. Several co-occurrence-based metrics have been proposed to measure bias amplification in classification datasets. The…

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