Unverified50% confidenceFactExact time
优先经验回放（PER）由Schaul等人于2015年提出，采样概率正比于TD误差绝对值加小常数，并用重要性采样权重修正分布偏移
1
Sources
50%
Confidence
Long-term
Relevance
8/20/2026
First Seen
Sources
Related Claims
UnverifiedAssuming the data follows a Gaussian distribution, maximizing the likelihood is equivalent to minimizing the mean squared error.61% similarUnverifiedIndustry experience shows that data quality is far more important than quantity in the SFT stage, and a small number of carefully annotated high-quality samples often outperforms a large number of low-quality samples.61% similarVerifiedThrough experiments on multi-hop reasoning benchmarks such as HotpotQA and FEVER, the ReAct paper demonstrated that compared to pure Chain-of-Thought reasoning, ReAct improved accuracy by approximately 10%–30% on tasks requiring external information retrieval.61% similarUnverified置换检验通过大量随机置换（通常1000到10000次）构建零假设下的经验分布来估计p值，无需参数假设但计算成本相对较高60% similarUnverified对同一测试用例执行多次调用统计成功比例得到通过率，比二元的通过/失败判断更能反映模型真实表现60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/778671API
curl https://kongchang.com/api/v1/knowledge/claims/778671MCP
get_claim(id=778671)