Владислав Уткин
Language-only reasoning models are typically created through supervised fine-tuning (SFT) or reinforcement learning (RL): SFT is simpler but requires large amounts of expensive reasoning trace data, while RL reduces data requirements at the cost of significantly increased training complexity and compute. Multimodal reasoning models follow a similar process, but the design space is more complex. With a mid-fusion architecture, the first decision is whether the base language model is itself a reasoning or non-reasoning model. This leads to several possible training pipelines:，这一点在新收录的资料中也有详细论述
，详情可参考新收录的资料
Unfortunately, WebKit supports AV1 only on newer devices that have a hardware decoder. Chrome supports it with a fallback to a software implementation when hardware acceleration is not available.
// Update all x values — contiguous memory access, cache-friendly，详情可参考新收录的资料