Expired80% confidenceFactTime unknown
The candidate's team used an internal platform based on DeepSeek's underlying model to generate test cases, employing the Harness framework and using Skills and Rules to constrain the large model's output.
1
Sources
80%
Confidence
Medium-term (~90 days)
Relevance
5/31/2026
First Seen
Valid until: 8/29/2026(expired)
Sources
6年测试工程师模拟面试复盘:三大致命问题及改进方法
bilibili软件测试黄老师
Related Entities
Related Claims
UnverifiedDeepSeek++'s Skill system supports configuring parameters such as model selection, manual/automatic mode, whether to use internet access, and deep thinking mode.76% similarUnverifiedDeepSeek open-sourced its trained model weights, training data recipe, and technical report.74% similarUnverifiedDeepSeek's MTP base-version draft model is co-optimized during main model training to align the draft model's output distribution with the target model, distinguishing it from post-hoc distillation approaches.73% similarUnverified缩放定律表明模型在特定任务上的表现与训练数据量、模型参数量和计算量之间存在幂律关系,OpenAI、DeepMind等机构的研究支持这一发现72% similarUnverifiedDeepSpec集成三大主流Draft Model算法、九个Hugging Face预训练Checkpoint和九个评测基准72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/5560API
curl https://kongchang.com/api/v1/knowledge/claims/5560MCP
get_claim(id=5560)