Awesome-Multimodal-Large-Language-Models
A curated, regularly updated reading list of papers and the author's own reading notes on multimodal large language models, large language models, and diffusion models.
Awesome-Multimodal-Large-Language-Models is a curated repository of research papers on multimodal large language models, large language models, and diffusion models, maintained by a PhD student in pattern recognition. Most entries link to the maintainer's own reading notes rather than only the paper itself.
Recent updates cover topics such as agentic and reinforcement-learning approaches to multimodal reasoning, models that think by manipulating images during inference, multimodal reward modeling with reinforcement learning, benchmarks for unified multimodal models, large human-annotated preference datasets for multimodal alignment, and image-perception benchmarks, along with links to the maintainer's own released models and benchmark code.