Verbose, non terminating CoT is currently common problem with open weight models based on R1-zero methods. Currently it seems that this shift of cost to infere

Verbose, non terminating CoT is currently common problem with open weight models based on R1-zero methods. Currently it seems that this shift of cost to inference-time is a necessary tradeoff that we have to live with (for now at least). It's more of a problem for many people running those models locally because they have constrained hardware that can't handle those long contexts. It seems that this paper shows not only that their method is cheaper in terms of fine tuning but also significantly reduces inference time cost for CoTs. If what they say gets confirmed it looks to me like quite significant contribution?