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Found 4 Skills
Writes rigorous mathematical proofs for ML/AI theory. Use when asked to prove a theorem, lemma, proposition, or corollary, fill in missing proof steps, formalize a proof sketch, 补全证明, 写证明, 证明某个命题, or determine whether a claimed proof can actually be completed under the stated assumptions.
Own experiment evidence semantics: decide datasets, baselines, metrics, ablations, robustness tests, chart evidence, and exactly what rows or columns a result table should contain. Use for experiment design, benchmark planning, supplied-result evidence structure, result-table schema, chart-spec semantics, 设计实验, 对比实验, 消融, 结果表证据结构. Do not search literature as the main deliverable, visually beautify or render an already specified table/figure, improve layout/colors/readability, or invent results.
Decompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding.
Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.