4 papers
Limits of PRM-Guided Tree Search for Mathematical Reasoning with LLMs
Tristan Cinquin, Geoff Pleiss, Agustinus Kristiadi
While chain-of-thought prompting with Best-of-N (BoN) selection has become popular for mathematical reasoning in large language models (LLMs), its linear structure fails to capture…
Language Models For Generalised PDDL Planning: Synthesising Sound and Programmatic Policies
Dillon Z. Chen, Johannes Zenn, Tristan Cinquin +1
We study the usage of language models (LMs) for planning over world models specified in the Planning Domain Definition Language (PDDL). We prompt LMs to generate Python programs th…
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks
Tristan Cinquin, Robert Bamler
Bayesian neural networks (BNN) promise to combine the predictive performance of neural networks with principled uncertainty modeling important for safety-critical systems and decis…
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning
Tristan Cinquin, Marvin Pförtner, Vincent Fortuin +2
Laplace approximations are popular techniques for endowing deep networks with epistemic uncertainty estimates as they can be applied without altering the predictions of the trained…