3 papers
cs.CL2026
Masked Language Flow Models
Iskander Azangulov, Kianoosh Ashouritaklimi, Leo Zhang +2
Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approximation that breaks down in th…
cs.LG2025
Active Learning with Task-Driven Representations for Messy Pools
Kianoosh Ashouritaklimi, Tom Rainforth
Active learning has the potential to be especially useful for messy, uncurated pools where datapoints vary in relevance to the target task. However, state-of-the-art approaches to…
cs.LG2024
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…