MM1.5: Methods, Analysis and Insights from Multimodal LLM Fine-tuning

Machine learning researcher at Apple working on large multimodal foundation models, video generation, and vision-language systems.

Research scientist at Apple Foundation Models working on generative AI, large language models, and multimodal models.

Sam Dodge is an Apple AI/ML-affiliated researcher. The linked arXiv paper lists him as a coauthor of MM1 and shows his affiliation as Apple AI/ML in Cupertino, California.

Research scientist at Apple Foundation Models with interests in natural language processing, structured generation, controllable generation, and algorithmic efficiency.

Research scientist at Apple working on large language models, vision-language models, and model scaling.

Researcher working on machine learning, vision and language, computer vision, diffusion, and generative AI.

Research scientist at Apple working on language and vision-language modeling, AI agents, and post-training.

Haotian Zhang is a research scientist on Apple AI/ML's Visual Intelligence team. His homepage says he works on embodied agents that understand the world from 2D and 3D image data as well as natural language, previously interned at Microsoft Research and Azure AI, completed a PhD in electrical and computer engineering at the University of Washington in 2022, and earlier earned master's degrees at Washington and a bachelor's degree at Shanghai Jiao Tong University.

Senior researcher at Apple working on large models, multimodal learning, and speech processing, according to his personal site.

Research scientist at Apple focused on state-of-the-art machine learning and computer vision methods.

Research scientist at Apple focused on natural language processing and machine learning.

Researcher working on machine learning, optimization, and sequential data.

Nina Wenzel is listed as an author of the Apple technical report MM1.5: Methods, Analysis and Insights from Multimodal LLM Fine-tuning.

Research scientist at Apple Foundation Models working on efficient training and multimodal language models.

Research scientist at Apple specializing in post-training, reinforcement learning, and AI agents.

Research scientist whose public OpenReview profile lists work on multimodal representation learning, speech synthesis, and personalized voice generation.

AI and machine learning engineer at Apple working on multimodal foundation models; previously worked at Snap and the University of Southern California.

Zhengfeng Lai is an ML Research Scientist at Apple AI/ML. His self-authored CV lists a PhD in Electrical and Computer Engineering from the University of California, Davis, prior Apple internship work, and publications in multimodal and vision-language learning.

Research scientist on Apple Foundation Models whose work focuses on machine learning systems, multimodal foundation models, and AI agents.

Research scientist at Apple focused on computer vision, multimodal learning, and robotics.

Canonical link

Zhe Gan

Jean-Philippe Fauconnier

Sam Dodge

Philipp Dufter

Bowen Zhang

Dhruti Shah

Xianzhi Du

Haotian Zhang

Zirui Wang

Peter Grasch

Yinfei Yang

Mingfei Gao

Nina Wenzel

Forrest Huang

Keen You

Aleksei Timofeev

Hong-You Chen

Zhengfeng Lai

Haoxuan You

Afshin Dehghan