activity
20242026
collaborators

6 papers

cs.CL2026

FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation

Rob Cornish, Iacopo Ghinassi, Po-Hung Yeh +7

Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to assess the faithfulness of these sy…

stat.CO2026

A categorical account of the Metropolis-Hastings algorithm

Rob Cornish, Andi Q. Wang

Metropolis-Hastings (MH) is a foundational Markov chain Monte Carlo (MCMC) algorithm. In this paper, we ask whether it is possible to formulate and analyse MH in terms of categoric…

quant-ph2026

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis

Richie Yeung, Aleks Kissinger, Rob Cornish

We consider the problem of synthesizing Clifford quantum circuits for devices with all-to-all qubit connectivity. We approach this task as a reinforcement learning problem in which…

cs.LG2025

SymDiff: Equivariant Diffusion via Stochastic Symmetrisation

Leo Zhang, Kianoosh Ashouritaklimi, Yee Whye Teh +1

We propose SymDiff, a method for constructing equivariant diffusion models using the framework of stochastic symmetrisation. SymDiff resembles a learned data augmentation that is d…

stat.ML2025

Stochastic Neural Network Symmetrisation in Markov Categories

Rob Cornish

We consider the problem of symmetrising a neural network along a group homomorphism: given a homomorphism , we would like a procedure that converts -equivariant neu…

cs.LG2024

Neural Network Symmetrisation in Concrete Settings

Rob Cornish

Cornish (2024) recently gave a general theory of neural network symmetrisation in the abstract context of Markov categories. We give a high-level overview of these results, and the…