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cs.CL2026
Sumi: Open Uniform Diffusion Language Model from Scratch
Mengyu Ye, Keito Kudo, Wataru Ikeda +3
Diffusion models have become a promising alternative to autoregressive models. Among these, uniform diffusion language models (UDLMs) permit any token to be updated at any step, in…
cs.CL2026
Reconsidering Positional Supervision in Masked Diffusion Language Model Training
Mengyu Ye, Keito Kudo, Ryosuke Takahashi +1
Masked diffusion language models (MDLMs) generate text by unmasking tokens in parallel and have recently emerged as alternatives to autoregressive language models. They can be view…
cs.CL2023
A Challenging Multimodal Video Summary: Simultaneously Extracting and Generating Keyframe-Caption Pairs from Video
Keito Kudo, Haruki Nagasawa, Jun Suzuki +1
This paper proposes a practical multimodal video summarization task setting and a dataset to train and evaluate the task. The target task involves summarizing a given video into a…