Trevor Ashby — accepted AI-conference papers

2024

Holistic Evaluation for Interleaved Text-and-Image Generation

Minqian Liu, Zhiyang Xu, Zihao Lin, Trevor Ashby, Joy Rimchala, Jiaxin Zhang +1

EMNLP 2024main

Interleaved text-and-image generation has been an intriguing research direction, where the models are required to generate both images and text pieces in an arbitrary order. Despite the emerging advancements in interleaved generation, the progress in its evaluation still significantly lags behind. E…

Cited by 6 Source ↗PDF ↗Scholar ↗

2024

Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning

Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin +3

ACL 2024findings

Despite vision-language models’ (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking task diversity in pretraining and visual instruction tuning, and (2) annotation error and bias in GPT-4 synthesized instru…

Cited by 34 Source ↗PDF ↗Scholar ↗