✨ 3 models: 7B/32B/ Mix-3-32B (MIT license) ✨ Dataset: 35 verifiable logic tasks (Sudoku, Cipher, Arrow Maze etc.) ✨ RL training with auto-verifiable rewards ✨ Generalizes to math without explicit math training ✨ +6 pts on BBEH, +9.5 on KOR-Bench vs baselines
✨ Apache 2.0 ✨ Handles up to 10,000+ frames on a single GPU ✨ 2048-frame encoding in just 12s ✨ Efficient Chunk-based Prefilling & Bi-granularity KV decoding
🔥 New benchmark & dataset for Subject-to-Video generation
OPENS2V-NEXUS by Pekin University ✨ Fine-grained evaluation for subject consistency BestWishYsh/OpenS2V-Eval ✨ 5M-scale dataset: BestWishYsh/OpenS2V-5M ✨ New metrics – automatic scores for identity, realism, and text match
✨Emotion-controlled, high-dynamic avatar videos ✨Multi-character support with separate audio control ✨Works with any style: cartoon, 3D, real face, while keeping identity consistent