This experiment is quite interesting, especially since only about 0.016% of the model weights were modified, achieving such a significant performance improvement.
However, I'm rather curious: Does this improvement come from the enhancement of the model's reasoning ability itself, or is it mainly due to the fixed issue of the model repeatedly reasoning and being unable to conclude normally?
However, I'm rather curious: Does this improvement come from the enhancement of the model's reasoning ability itself, or is it mainly due to the fixed issue of the model repeatedly reasoning and being unable to conclude normally?