Gowthami Somepalli

@gowthami.bsky.social

PhD-ing at UMD. Knows a little about multimodal generative models. Check out my website to know more - https://somepago.github.io/

The recording of my #NeurIPS2024 workshop talk on multimodal iterative refinement is now available to everyone who registered: neurips.cc/virtual/2024... My talk starts at 1:10:45 into the recording. I believe this will be made publicly available eventually, but I'm not sure when exactly!

Adaptive Foundation Models: Evolving AI for Personalized and Efficient LearningNeurIPS 2024

neurips.cc

Paul Vicol@paulvicol.bsky.social · 2y ago

@sedielem.bsky.social speaking now on Multimodal Iterative Refinement at the Adaptive Foundation Models workshop!

Trying to build a "books you must read" list for my lab that everyone gets when they enter. Right now its: - Sutton and Barto - The Structure of Scientific Revolutions - Strunk and White - Maybe "Prediction, Learning, and Games", TBD Kinda curious what's missing in an RL / science curriculum

This is a simple and good paper, which somehow nobody working on these things cites, or even seems to be aware of arxiv.org/abs/2406.05213 It is simple idea that seems useful; it formulates the subjective uncertainty for natural language generation in a decision-theoretic setup.

On Subjective Uncertainty Quantification and Calibration in Natural Language Generation

Applications of large language models often involve the generation of free-form responses, in which case uncertainty quantification becomes challenging. This is due to the need to identify task-specif...

arxiv.org

let me say it once more: "the gap between OAI/Anthropic/Meta/etc. and a large group of companies all over the world you've never cared to know of, in terms of LM pre-training? tiny"

Bild

Interesting paper on arxiv this morning: arxiv.org/abs/2411.13683 It's a video masked autoencoder in which you learn which tokens to mask to process fewer of them and scale to longer videos. It's a #NeurIPS2024 apparently. I wonder if there could be such strategy in the pure generative setup.

Extending Video Masked Autoencoders to 128 frames

Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked Autoencoders (MAE) ...

arxiv.org

Discrete diffusion has become a very hot topic again this year. Dozens of interesting ICLR submissions and some exciting attempts at scaling. Here's a bibliography on the topic from the Kuleshov group (my open office neighbors). github.com/kuleshov-gro...

GitHub - kuleshov-group/awesome-discrete-diffusion-models: A curated list for awesome discrete diffusion models resources.

A curated list for awesome discrete diffusion models resources. - kuleshov-group/awesome-discrete-diffusion-models

github.com

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6 years ago, in the days of GAN art, I wrote an article called "Can Computers Create Art?", arguing that computers should not be considered artists, regardless of how good image generation gets. People sometimes ask if my views have changed. I say, 1/🧵 www.mdpi.com/2076-0752/7/...

Can Computers Create Art?

This essay discusses whether computers, using Artificial Intelligence (AI), could create art. First, the history of technologies that automated aspects of art is surveyed, including photography and an...

mdpi.com