Many LM applications may be formulated as text generation conditional on some (Boolean) constraint.
Generate a…
- Python program that passes a test suite.
- PDDL plan that satisfies a goal.
- CoT trajectory that yields a positive reward.
The list goes on…
How can we efficiently satisfy these? 🧵👇
13.05.2025 14:22 — 👍 11 🔁 6 💬 1 📌 0
Correction: poster number is 634 :)
26.04.2025 01:21 — 👍 0 🔁 0 💬 0 📌 0
ICLR 2025 Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo OralICLR 2025
Come find us at #ICLR this Saturday
Oral: 4:30pm (Garnet 213-215, session 6B)
Poster: 10am-12:30pm #634 (Hall 2B)
iclr.cc/virtual/2025...
25.04.2025 19:35 — 👍 3 🔁 0 💬 1 📌 0
GitHub - genlm/genlm-control: Controlled text generation with programmable constraints.
Controlled text generation with programmable constraints. - genlm/genlm-control
- Cast controlled generation as an inference problem, with the LM as a prior and verifiers and scorers as likelihood
- Use Sequential Monte Carlo to sample from the resulting posterior
Library w/ tutorials for setting up your own controlled generation inference problems: github.com/genlm/genlm-...
25.04.2025 19:35 — 👍 3 🔁 1 💬 1 📌 0
#ICLR2025 Oral
How can we control LMs using diverse signals such as static analyses, test cases, and simulations?
In our paper “Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo” (w/ @benlipkin.bsky.social,
@alexlew.bsky.social, @xtimv.bsky.social) we:
25.04.2025 19:33 — 👍 7 🔁 6 💬 1 📌 0
Law Prof. GWU, Tech & Justice. Author: “Your Data Will Be Used Against You,” “The Rise of Big Data Policing,” “Why Jury Duty Matters,” and “The Law of Law School.”
Statistician | Assistant professor @ Brown University Dept of Biostatistics | Developing nonparametric Bayesian methods for causal inference.
Research site: stablemarkets.netlify.app
#statsky
Blog: https://argmin.substack.com/
Webpage: https://people.eecs.berkeley.edu/~brecht/
Lecturer in Maths & Stats at Bristol. Interested in probabilistic + numerical computation, statistical modelling + inference. (he / him).
Homepage: https://sites.google.com/view/sp-monte-carlo
Seminar: https://sites.google.com/view/monte-carlo-semina
causal inference, econometrics, ML, arsenal, loud music, unix, FOSS for scientific computing.
apoorvalal.github.io
(passively) maintains @paperposterbot.bsky.social
Associate Professor of Machine Learning, University of Oxford;
OATML Group Leader;
Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
Assistant Prof of Computer Science and Data Science at UChicago. Research on visualization, HCI, statistics, data cognition. Moonlighting as a musician 🎺 https://people.cs.uchicago.edu/~kalea/
Associate Professor @Harvard SEAS. Information theorist, but only asymptotically.
Assistant prof at TU Graz, formerly assistant prof at TU Eindhoven, Marie-Curie Fellow at University of Cambridge. Probabilistic Machine Learning.
Machine Learning PhD Student
@ Blei Lab & Columbia University.
Working on probabilistic ML | uncertainty quantification | LLM interpretability.
Excited about everything ML, AI and engineering!
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him
👉 https://april-tools.github.io
http://timvieira.github.io/blog
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
Assistant professor of CS at UC Berkeley, core faculty in Computational Precision Health. Developing ML methods to study health and inequality. "On the whole, though, I take the side of amazement."
https://people.eecs.berkeley.edu/~emmapierson/
Postdoctoral fellow at Harvard Data Science Initiative | Former computer science PhD at Columbia University | ML + NLP + social sciences
https://keyonvafa.com
Assistant Professor of Statistics & Data Science at UChicago
Topics: data-intensive social science, Bayesian statistics, causal inference, probabilistic ML
Proud “golden retriever” 🦮
I study algorithms/learning/data applied to democracy/markets/society. Asst. professor at Cornell Tech. https://gargnikhil.com/. Helping building personalized Bluesky research feed: https://bsky.app/profile/paper-feed.bsky.social/feed/preprintdigest
