Unverified50% confidenceFactExact time
According to 2020 Papers With Code statistics, even for papers that provide official code, approximately 30% still exhibit significant performance fluctuations when run on different machines or with different random seeds.
1
Sources
50%
Confidence
Long-term
Relevance
8/16/2026
First Seen
Sources
复现TS-JEPA踩坑：从0%到74%控制精度的差距在哪
Related Claims
UnverifiedResearch shows that structured prompts, compared to casual descriptions, can improve the first-pass rate of code generation from 30% to over 70%70% similarUnverified2024 年的多项基准测试表明，经过严格安全对齐的模型在代码生成任务上的拒绝率比基座模型高出 15-30%，在创意写作任务上的自我审查率高达 40%67% similarUnverified斯坦福大学2023年的研究表明，引入明确的需求分析和设计阶段后，LLM生成代码的功能正确率提升约30%65% similarUnverifiedEven with the most advanced code models, when they claim 'the code has passed testing,' the actual pass rate may be below 70%.64% similarUnverifiedA 2023 study found that mainstream code models exhibit a hallucination rate of 15–25% when generating API calls, which is especially prominent when involving newer or more obscure libraries.64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/756926API
curl https://kongchang.com/api/v1/knowledge/claims/756926MCP
get_claim(id=756926)