Showing papers from UPenn / Apple Show all papers
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.
Normalizing Trajectory Models train expressive conditional normalizing flows for coarse diffusion steps with exact trajectory likelihood, enabling high-quality four-step text-to-image generation.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 13 on Hugging Face
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.
STARFlow2 unifies multimodal generation by vertically interleaving a pretrained vision-language model with an autoregressive normalizing flow under shared causal masking, enabling cache-friendly interleaved text-image generation with strong benchmark performance.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 13 on Hugging Face
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.