Check out this awesome work: well-curated data is and will continue to be key for superhuman LLM performance
23.04.2025 20:34 — 👍 1 🔁 0 💬 0 📌 0
Tons of model weights available, but what else can we do besides prediction? 🤔 Introducing Grad-Mimic! A new data selection framework using well-trained model’s weights to find high-value samples for foundation models. Boost data curation & data efficiency!
09.02.2025 21:07 — 👍 3 🔁 3 💬 1 📌 0
What enables a strong model to surpass its weaker teacher?
🚀 Excited to share our ICLR 2025 paper: "Weak-to-Strong Generalization Through the Data-Centric Lens"! 🧵
05.02.2025 18:22 — 👍 4 🔁 2 💬 1 📌 0
Brown CS '24 | San Francisco Bay Area | He/Him
"I'm just like, dude, like, oh, my god, like, can we talk about, like, the political and economic state of the world right now?" -Jaden Smith
PhD student @Yale • Applied Scientist @AWS AI • Automated Reasoning • Neuro-Symbolic AI • Alignment • Security & Privacy • Views my own • https://ferhat.ai
go bears!!!
jessicad.ai
kernelmag.io
CS PhD student @UW-Madison, interested in statistical machine learning and optimization
Previously Applied Math/Stats @UChicago
AI @ OpenAI, Tesla, Stanford
CS PhD student @ UW Madison. Working on data and compute efficient LLM adaptation.
STAT PhD @ Wisc | Working on social network analysis & LLM adaptation
Ph.D. Candidate at UW-Madison
https://harit7.github.io/
Ph.D student at @WisconsinCS @UWMadison
Ph.D. student at UW-Madison. Working on automating foundation model guided science. Previously at CMU, UCSD, Fresno City College.
https://nick11roberts.science
Professor @UCLA, Research Scientist @ByteDance | Recent work: SPIN, SPPO, DPLM 1/2, GPM, MARS | Opinions are my own
Recently a principal scientist at Google DeepMind. Joining Anthropic. Most (in)famous for inventing diffusion models. AI + physics + neuroscience + dynamical systems.
web: http://maxim.ece.illinois.edu
substack: https://realizable.substack.com
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst.
Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org
I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
Blog: https://argmin.substack.com/
Webpage: https://people.eecs.berkeley.edu/~brecht/
