🎓 Hats off to the 2025 IICD graduates: Yining Ma Junze Huang Yichi Yang Ruilin Dai Boan Zhu Cameron Park @jlfan.bsky.social & Achille Nazaret! Wishing you all the best in your next chapter — we’re proud of you! 💙 #Columbia2025 @bleilab.bsky.social @khanhndinh.bsky.social @elhamazizi.bsky.social
Nicolas Beltran-Velez
@velezbeltran.bsky.social
Machine Learning PhD Student @ Blei Lab & Columbia University. Working on probabilistic ML | uncertainty quantification | LLM interpretability. Excited about everything ML, AI and engineering!
this is probably not the complete picture of KD, but i can definitely sleep better after writing down and confirming this minimal working explanation. arXiv: arxiv.org/abs/2505.13111 (3/4)
Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation
Knowledge distillation (KD) is a core component in the training and deployment of modern generative models, particularly large language models (LLMs). While its empirical benefits are well documented-...
arxiv.org
I received a review like this five years ago. It’s probably the right time now to share it with everyone who wrote or got random discouraging reviews from ICML/ACL.
First 11 chapters of RLHF Book have v0 draft done. Should be useful now. Next: * Crafting more blog content into future topics, * DPO+ chapter, * Meeting with publishers to get wheels turning on physical copies, * Cleaning & cohesiveness rlhfbook.com
🔥 Benchmark Alert! MotifBench sets a new standard for evaluating protein design methods in motif scaffolding. Why does this matter? Reproducibility & fair comparison have been lacking—until now. Paper: arxiv.org/abs/2502.12479 | Repo: github.com/blt2114/Moti... A thread ⬇️
The HuggingFace/Nanotron team just shipped an entire pretraining textbook in interactive format. huggingface.co/spaces/nanot... It’s not just a great pedagogic support, but many unprecedented data and experiments presented for the first time in a systematic way.
Good God, please. I just want some gradients that don't vanish 😭
I was hoping that recent events would lead to a mass exodus from X. Many have left, but most of the ML and LLM people have not. I have lost a lot of respect for the ML community.
Now that bluesky has gifs (it didn't work?), I can share (again) my educational notebook on discrete flow matching (by Itai Gat et al.). Also please check the original article and official implementation by Meta! 🐍 github.com/gle-bellier/... 🐍 github.com/facebookrese... 📄 arxiv.org/abs/2407.15595
Really excited about this! We note a connection between diffusion/flow models and neural/latent SDEs. We show how to use this for simulation-free learning of fully flexible SDEs. We refer to this as SDE Matching and show speed improvements of several orders of magnitude. arxiv.org/abs/2502.02472
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
The Latent Stochastic Differential Equation (SDE) is a powerful tool for time series and sequence modeling. However, training Latent SDEs typically relies on adjoint sensitivity methods, which depend ...
arxiv.org
I have a sinking feeling that by 2029 I'm going to be faking a British accent so no one will think I was one of the *Americans* working on AI during the regime.
NGL, it's kind of surprising that more people haven't migrated here, especially given what Musk has been doing these days. I don't get it.
Since everyone wants to learn RL for language models now post DeepSeek, reminder that I've been working on this book quietly in the background for months. Policy gradient chapter is coming together. Plugging away at the book every day now. rlhfbook.com/c/11-policy-...
Please stop anthropomorphizing language models, it makes them feel really bad
This comments section is the first time I've felt even a shred of hope in eight days.
From the fednews community on Reddit
Explore this post and more from the fednews community
reddit.com
Nazi salutes and speaking at neo-Nazi rallies seems bad. There's history that we should learn from.
Something I really like about NLP research is that it makes everything super intuitive. This week I have been thinking about variational inference in NLP and a lot of the things that seemed to require mathematical intuition just become trivial when thinking about language. So cool:)
New randomized, controlled trial by the World Bank of students using GPT-4 as a tutor in Nigeria. Six weeks of after-school AI tutoring = 2 years of typical learning gains, outperforming 80% of other educational interventions. And it helped all students, especially girls who were initially behind.
Does anyone have any good resources to learn about quantization? Any essential papers to read and resources about how to use/quantize models in practice are greatly appreciated!
1-> 2 -> 3 -> 3.5 -> 4 -> 4o -> o1 -> o3 I guess we need AGI just to figure out how to name things
If you are into ML theory (RL or not) with a proven track record, and you are interested in an industry research position, PM me. Feel free to spread the word.
🧵 Excited to share #Echidna, a Bayesian framework for quantifying the impact of gene dosage on phenotypic plasticity: tinyurl.com/296kf7hf! With @elhamazizi.bsky.social and @mingxz.bsky.social, we integrate scRNA-seq & WGS to uncover how CNAs drive tumor evolution and transcriptional variability.
biorxiv.org
Proud of this work spearheaded by the phenomenal @jlfan.bsky.social and @mingxz.bsky.social in collaboration w/ Ben Izar! The past 3 years we've worked hard to unravel how #CNVs shape #tumor phenotypic plasticity seen in #singlecell #RNAseq data ➡️ #Echidna 🦔
🧵 Excited to share #Echidna, a Bayesian framework for quantifying the impact of gene dosage on phenotypic plasticity: tinyurl.com/296kf7hf! With @elhamazizi.bsky.social and @mingxz.bsky.social, we integrate scRNA-seq & WGS to uncover how CNAs drive tumor evolution and transcriptional variability.
Hello! We will be presenting Estimating the Hallucination Rate of Generative AI at NeurIPS. Come if you'd like to chat about epistemic uncertainty for In-Context Learning, or uncertainty more generally. :) Location: East Exhibit Hall A-C #2703 Time: Friday @ 4:30 Paper: arxiv.org/abs/2406.07457
I'm on my way to #NeurIPS2024. On Friday I'm going to present my latest paper with Yuval Benjamini. The gist is in the comments, and come chat with me to hear more!
The circuit hypothesis proposes that LLM capabilities emerge from small subnetworks within the model. But how can we actually test this? 🤔 joint work with @velezbeltran.bsky.social @maggiemakar.bsky.social @anndvision.bsky.social @bleilab.bsky.social Adria @far.ai Achille and Caro
I have been a little bit scarce on social media in the last few months. Some of that has just been from being busy at work, but some of it has had to do with my father's passing. He hated the very idea of social media, but he religiously followed my Twitter, and then Bluesky, feeds. /n