Unverified50% confidenceFactExact time
The paper explicitly states that it is not proposing a new regression algorithm, nor claiming performance improvements in trained models, but rather answering the foundational theoretical question of what future updates actually reveal.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe study does not deny the value of reasoning-type models, holding that their performance improvements are real; what it denies is the way in which those improvements are explained.73% similarUnverified提示词并没有真正提高模型的能力,它只是给模型提供了更多相关信息71% similarUnverifiedThe author believes that the 'Chain-of-Thought' output of LLMs is more likely a highly fitted reproduction of reasoning patterns in training data, rather than genuine logical deduction in the true sense.70% similarUnverified提示词工程本质上是利用模型已有能力提供更多相关信息,并未扩展模型的能力边界68% similarUnverifiedThe community speculates that large-scale reasoning chain distillation partly explains the success of certain models' RL training, but this is speculation rather than a definitive causal conclusion from the paper.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1002209API
curl https://kongchang.com/api/v1/knowledge/claims/1002209MCP
get_claim(id=1002209)