Unverified50% confidenceOpinionExact time
Arun认为一个为优秀推理训练的模型不可能同时擅长检索，因为推理和检索会争夺参数空间
1
Sources
50%
Confidence
Long-term
Relevance
7/15/2026
First Seen
Sources
Related Claims
UnverifiedPure reasoning models like Chain of Thought cannot access external tools and may reach wrong conclusions due to gaps in training data.76% similarUnverified设计判断力这类偏主观的能力很难通过统一基准测试量化73% similarUnverifiedPrompt engineering techniques such as chain-of-thought, few-shot prompting, and self-consistency cannot enable a model to access information beyond its training cutoff date, cannot guarantee the precision of floating-point arithmetic, and cannot handle external files the model has never seen.71% similarUnverifiedThe root cause of rising hallucination rates in reasoning models is misaligned incentives: reinforcement learning training causes models to tend to generate detailed and persuasive chains of thought, and human evaluators give higher scores to more elaborately argued answers, even when they contain factual errors.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/520978API
curl https://kongchang.com/api/v1/knowledge/claims/520978MCP
get_claim(id=520978)