13 tagged ai generated content, measured the same way as everything else here.
Browse within: ai-scientist 12autoresearch 12forensics 12llm-agents 12peer-review 12
Skill Claude CodeCodex
Audit whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent…
Skill Claude CodeCodex
Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan…
Skill Claude CodeCodex
MEMO-ONLY prior-work overlap advisory: surfaces the two ADVISORY taxonomy signals neither a tool nor a model can decide from the paper alone — ADV-TRIVIAL-COMBINATION (standard A+B+C / 缝合 stapling) and ADV-DUPLICATE-PUBLICATION (repackaged / duplicate submission). The executor RETRIEVES candidate prior work (DBLP…
Skill Claude CodeCodex
Use when editing or reviewing text to remove AI-generated patterns and make writing more natural and human. Use when the user provides text and asks to remove AI tone, humanize, rewrite naturally, or polish. Also use when text is clearly AI-generated Chinese content. 適用於使用者要求「去 AI 味」、「人性化」、「改寫得更自然」、「潤稿」、「改得像人寫的」時。.