6 papers · 1 filter
ORCA: Hunting Compositional Failures in Text-to-Image Diffusion
Arshia Hemmat, Amirhossein Vahidi, Amitis Shidani +4
Text-to-image diffusion models fail predictably on compositional prompts: attributes bind to the wrong objects, spatial relations invert, and multi-object scenes lose count. Recent…
On Trajectory-Aware Training for Masked Diffusion Language Models
Manuel Madeira, Amitis Shidani, Alice Bizeul +6
Masked diffusion models (MDMs) generate text by unmasking several tokens per step, but they are trained and sampled under different conditions. The model is trained on randomly mas…
Limits of Confidence in Diffusion
Russ Webb, Amitis Shidani, Alice Bizeul +1
Discrete diffusion, including remasking and uniform-state samplers, generate a sequence by writing multiple token positions per step, drawing each from a per-position distribution…
Scaling Categorical Flow Maps
Oscar Davis, Anastasiia Filippova, Pierre Ablin +4
Continuous diffusion and flow matching models could represent a powerful alternative to autoregressive approaches for language modelling (LM), as they unlock a host of advantages c…
Scaling Properties of Continuous Diffusion Spoken Language Models
Jason Ramapuram, Eeshan Gunesh Dhekane, Amitis Shidani +6
Speech-only spoken language models (SLMs) lag behind text and text-speech models in performance, with recent discrete autoregressive (AR) SLMs indicating significant computational…
The Design Space of Tri-Modal Masked Diffusion Models
Louis Bethune, Victor Turrisi, Bruno Kacper Mlodozeniec +21
Discrete diffusion models have emerged as strong alternatives to autoregressive language models, with recent work initializing and fine-tuning a base unimodal model for bimodal gen…