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:
Девять детей отправились в больницу после посещения бассейна в российском городе08:49
。新收录的资料是该领域的重要参考
Юлия Мискевич (Ночной линейный редактор)
Standard Digital，这一点在新收录的资料中也有详细论述
FT App on Android & iOS。新收录的资料是该领域的重要参考
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