#probabilistic-programming News & Analysis

2 articles tagged with #probabilistic-programming. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 107/10

🧠

Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models

Researchers introduce Program-based Posterior Training (PPT), a novel fine-tuning method that uses probabilistic programs to train LLMs on inductive reasoning tasks. By generating synthetic scenarios and using probabilistic inference to create distributional targets, the approach significantly improves model accuracy on uncertainty estimation while better aligning with human judgment.

AINeutralarXiv – CS AI · Apr 106/10

🧠

One Life to Learn: Inferring Symbolic World Models for Stochastic Environments from Unguided Exploration

Researchers introduce OneLife, a framework for learning symbolic world models from minimal unguided exploration in complex, stochastic environments. The approach uses conditionally-activated programmatic laws within a probabilistic framework and demonstrates superior performance on 16 of 23 test scenarios, advancing autonomous construction of world models for unknown environments.