This repository is an awesome list curating research papers on Video-LMM Post-Training for video reasoning. It maintains a JSON dataset of paper metadata (title, release date, links, tags, etc.) and uses a Python script to generate a categorized README.md with markdown tables organized by research paradigm (Reinforced Video-LMMs, SFT for Reasoning, Test-Time Scaling, Benchmarks, Surveys). The repository serves as a reference tracker for the latest advancements in enhancing reasoning capabilities of video-focused multimodal models through post-training techniques. The hybrid nature lies in its dual role as both a data collection (the JSON paper metadata) and a lightweight data presentation system (the generation script).