João Loula
@joaoloula.bsky.social
PhD student @probcompproj and @MITCoCoSci, working on scaling data science using probabilistic programming.
Reposted by João Loula
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? 🧵👇
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? 🧵👇
May 13, 2025 at 2:22 PM
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? 🧵👇
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? 🧵👇
#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:
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:
April 25, 2025 at 7:33 PM
#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:
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: