Manu Gaur

Hi, I'm a research assistant at CVIT, IIIT-H under Dr. Makarand Tapaswi. I recently graduated from Delhi Technological University with a major in Applied Physics. I am originally from New Delhi, India.

At Google I've worked on Glass, Lens Blur, HDR+, VR, Portrait Mode, Portrait Light, and Maps. I did my PhD at UC Berkeley, where I was advised by Jitendra Malik. I've received the PAMI Young Researcher Award.

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• 2024-05: I joined FAIR, Meta for summer internship with Dr. Zhuang Liu, yayyyyy!
• 2024-04: I received OpenAI Superalignment Fellowship! Thank you OpenAI!!! Looking forward to the cool works.
• 2024-04: Our paper Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs was accepted at CVPR 2024 as an Oral Paper!
• 2024-01: Our paper Image Clustering in the Age of Pretrained Models was accepted at ICLR 2024!
• 2023-12: Our papers were accepted at CPAL 2024!
• 2023-09: I am helping organizing the QVCV workshop in ICCV. See you all in Paris!
• 2023-09: Our papers MultiMon and CRATE(whitebox-transformer) were accepted at NIPS 2023!
• 2023-07: Our paper Manifold Linearizing and Clustering was accepted at ICCV 2023!
• 2023-05: I graduated from UC Berkeley with triple degree Applied Math (Honor), Statistics (Honor) and Computer Science (No honor, because I didn't want to take 16b and 61c too early, but I published quite some interesting work so yay)!!!
• 2023-04: I will be a CS PhD student in NYU Courant advised by Professor Yann LeCun and Professor Saining Xie. Looking forward to working with Yann and Saining in New York!
• 2023-01: Our paper incremental-CTRL was accepted at ICLR 2023!

Research

I am interested in self-supervised learning, multimodal models, generative modelling and reinforcement learning. My long term goal is ...

MLLMs generate generic captions. We outperform MLLMs 30x size.

Closed source MLLMs struggle in capturing finegrained visual differences, with open-source models failing to outperform random guess.