Sweta Karlekar
swetakar.bsky.social
Sweta Karlekar
@swetakar.bsky.social
Machine learning PhD student @ Blei Lab in Columbia University

Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling!

Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams.

🔗 www.sweta.dev
Reposted by Sweta Karlekar
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
December 12, 2024 at 6:13 PM
Reposted by Sweta Karlekar
fun @bleilab.bsky.social x oatml collab

come chat with Nicolas , @swetakar.bsky.social , Quentin , Jannik , and i today
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
December 13, 2024 at 5:26 PM
Reposted by Sweta Karlekar
Check out our new paper from the Blei Lab on probabilistic predictions with conditional diffusions and gradient boosted trees! #Neurips2024
I am very excited to share our new Neurips 2024 paper + package, Treeffuser! 🌳 We combine gradient-boosted trees with diffusion models for fast, flexible probabilistic predictions and well-calibrated uncertainty.

paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...

🧵(1/8)
December 2, 2024 at 11:02 PM
Reposted by Sweta Karlekar
Check out our new paper about hypothesis testing the circuit hypothesis in LLMs! This work previously won a top paper award at the ICML mechanistic interpretability workshop, and we’re excited to share it at #Neurips2024
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
December 10, 2024 at 7:07 PM
Reposted by Sweta Karlekar
For anyone interested in fine-tuning or aligning LLMs, I’m running this free and open course called smol course. It’s not a big deal, it’s just smol.

🧵>>
December 3, 2024 at 9:21 AM
Very happy to share some recent work by my colleagues @velezbeltran.bsky.social, @aagrande.bsky.social and @anazaret.bsky.social! Check out their work on tree-based diffusion models (especially the website—it’s quite superb 😊)!
I am very excited to share our new Neurips 2024 paper + package, Treeffuser! 🌳 We combine gradient-boosted trees with diffusion models for fast, flexible probabilistic predictions and well-calibrated uncertainty.

paper: arxiv.org/abs/2406.07658
repo: github.com/blei-lab/tre...

🧵(1/8)
December 2, 2024 at 10:49 PM
Just learned about @andrewyng.bsky.social's new tool, aisuite (github.com/andrewyng/ai...) and wanted to share! It's a standardized wrapper around chat completions that lets you easily switch between querying different LLM providers, including OpenAI, Anthropic, Mistral, HuggingFace, Ollama, etc.
GitHub - andrewyng/aisuite: Simple, unified interface to multiple Generative AI providers
Simple, unified interface to multiple Generative AI providers - GitHub - andrewyng/aisuite: Simple, unified interface to multiple Generative AI providers
github.com
November 29, 2024 at 8:25 PM
Reposted by Sweta Karlekar
Test of Time Paper Awards are out! 2014 was a wonderful year with lots of amazing papers. That's why, we decided to highlight two papers: GANs (@ian-goodfellow.bsky.social et al.) and Seq2Seq (Sutskever et al.). Both papers will be presented in person 😍

Link: blog.neurips.cc/2024/11/27/a...
Announcing the NeurIPS 2024 Test of Time Paper Awards  – NeurIPS Blog
blog.neurips.cc
November 27, 2024 at 3:48 PM
Reposted by Sweta Karlekar
The Gini coefficient is the standard way to measure inequality, but what does it mean, concretely? I made a little visualization to build intuition:
www.bewitched.com/demo/gini
November 23, 2024 at 3:31 PM
Reposted by Sweta Karlekar
Interested in machine learning in science?

Timo and I recently published a book, and even if you are not a scientist, you'll find useful overviews of topics like causality and robustness.

The best part is that you can read it for free: ml-science-book.com
November 15, 2024 at 9:46 AM
Reposted by Sweta Karlekar
new paper from Anthropic on LLM evaluation recommendations

www.anthropic.com/research/sta...
A statistical approach to model evaluations
A research paper from Anthropic on how to apply statistics to improve language model evaluations
www.anthropic.com
November 22, 2024 at 12:47 PM
Reposted by Sweta Karlekar
Just realized BlueSky allows sharing valuable stuff cause it doesn't punish links. 🤩

Let's start with "What are embeddings" by @vickiboykis.com

The book is a great summary of embeddings, from history to modern approaches.

The best part: it's free.

Link: vickiboykis.com/what_are_emb...
November 22, 2024 at 11:13 AM
(Shameless) plug for David Blei's lab at Columbia University! People in the lab currently work on a variety of topics, including probabilistic machine learning, Bayesian stats, mechanistic interpretability, causal inference and NLP.

Please give us a follow! @bleilab.bsky.social
November 20, 2024 at 8:42 PM
Reposted by Sweta Karlekar
We created an account for the Blei Lab! Please drop a follow 😊

@bleilab.bsky.social
November 20, 2024 at 3:34 PM
Reposted by Sweta Karlekar
📢 Post-Bayesian online seminar series coming!📢
To stay posted, sign up at
tinyurl.com/postBayes
We'll discuss cutting-edge methods for posteriors that no longer rely on Bayes Theorem.
(e.g., PAC-Bayes, generalised Bayes, Martingale posteriors, ...)
Pls circulate widely!
Mailing list contact information
Information to be added to the post-Bayes mailing list.
tinyurl.com
November 19, 2024 at 8:22 PM
Reposted by Sweta Karlekar
Starter packs I found:
AI (*about* AI, not *for* an AI) go.bsky.app/SipA7it
Spoken Language Processing bsky.app/starter-pack...
Diversify Tech's pack bsky.app/starter-pack...
Women in Tech bsky.app/starter-pack...
Great UK Commentators bsky.app/starter-pack...
Linguistics bsky.app/starter-pack...
November 19, 2024 at 10:07 PM
I'm TAing for a class and wanted to put together a (short) list of papers that are a good, accessible intro for students to get started in mech interp. An ask for the community: what papers would you add / which papers am I missing? (1/n)
A Mathematical Framework for Transformer Circuits
transformer-circuits.pub
November 19, 2024 at 3:15 PM
If you’re interested in mechanistic interpretability, I just found this starter pack and wanted to boost it (thanks for creating it @butanium.bsky.social !). Excited to have a mech interp community on bluesky 🎉

go.bsky.app/LisK3CP
November 19, 2024 at 12:28 AM
For anyone looking for climate-related data for ML projects, I recently learned about www.saildrone.com/technology/d....
Saildrone builds ocean drones that collect a ton of oceanic and climate data. And they have some publicly-available datasets on their website for researchers :) 🌊 #mlsky
Browse Sample Data Sets – Saildrone
Browse publicly available sample data sets from completed Saildrone missions, available for download in NetCDF format.
www.saildrone.com
November 18, 2024 at 10:28 PM
Reposted by Sweta Karlekar
Nice article by @nedpotter.bsky.social includes a link to a BlueSky Directory of Starter Packs...
#AcademicSky #PhDSky
November 18, 2024 at 7:24 PM
Reposted by Sweta Karlekar
I made a starter pack for researchers in probabilistic machine learning.

DM/reply if you want to be added!

go.bsky.app/DuCtJqC
November 18, 2024 at 2:00 AM