longvila-scaling-rl-long-videos

Train vision-language models on hour-long videos using a two-stage pipeline combining supervised fine-tuning with GRPO, reaching 71% accuracy on VideoMME while supporting 8,192 frames through efficient multi-modal sequence parallelism.

Independent GitHub snapshot · Automated classification · Original documentation governs