Shobhita Sundaram
@shobsund.bsky.social
PhD student at MIT working on deep learning (representation learning, generative models, synthetic data, alignment).
ssundaram21.github.io
ssundaram21.github.io
Personal vision tasks–like detecting *your mug*--are hard; they’re data scarce and fine-grained.
In our new paper, we show you can adapt general-purpose vision models to these tasks from just three photos!
📝: arxiv.org/abs/2412.16156
💻: github.com/ssundaram21/...
(1/n)
In our new paper, we show you can adapt general-purpose vision models to these tasks from just three photos!
📝: arxiv.org/abs/2412.16156
💻: github.com/ssundaram21/...
(1/n)
December 23, 2024 at 5:26 PM
Personal vision tasks–like detecting *your mug*--are hard; they’re data scarce and fine-grained.
In our new paper, we show you can adapt general-purpose vision models to these tasks from just three photos!
📝: arxiv.org/abs/2412.16156
💻: github.com/ssundaram21/...
(1/n)
In our new paper, we show you can adapt general-purpose vision models to these tasks from just three photos!
📝: arxiv.org/abs/2412.16156
💻: github.com/ssundaram21/...
(1/n)
I'm at #NeurIPS2024 this week! Excited to present our work on perceptual alignment with Stephanie Fu on Thursday morning (poster #1302).
Please reach out if you want to chat about synthetic data, alignment, data-centric AI, representation learning, or anything else!
Please reach out if you want to chat about synthetic data, alignment, data-centric AI, representation learning, or anything else!
First up, "When Does Perceptual Alignment Benefit Vision Representations?" (arxiv.org/abs/2410.10817)
This paper is about distance between embeddings.
It says: measure how humans perceive distance, then adjust a neural net to match.
This improves transfer to lots of tasks (but not all tasks).
This paper is about distance between embeddings.
It says: measure how humans perceive distance, then adjust a neural net to match.
This improves transfer to lots of tasks (but not all tasks).
December 11, 2024 at 6:55 PM
I'm at #NeurIPS2024 this week! Excited to present our work on perceptual alignment with Stephanie Fu on Thursday morning (poster #1302).
Please reach out if you want to chat about synthetic data, alignment, data-centric AI, representation learning, or anything else!
Please reach out if you want to chat about synthetic data, alignment, data-centric AI, representation learning, or anything else!