4 papers
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…
SLVMEval: Synthetic Meta Evaluation Benchmark for Text-to-Long Video Generation
Ryosuke Matsuda, Keito Kudo, Haruto Yoshida +2
This paper proposes the synthetic long-video meta-evaluation (SLVMEval), a benchmark for meta-evaluating text-to-video (T2V) evaluation systems. The proposed SLVMEval benchmark foc…
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…
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…