Unverified50% confidenceFactExact time
Authorship attribution is a mature research direction in natural language processing, whose goal is to determine author identity based on textual features, with commonly used features including function word frequency, syntactic tree depth, punctuation distribution, and part-of-speech n-grams.
1
Sources
50%
Confidence
Long-term
Relevance
10/17/2026
First Seen
Sources
Related Entities
Related Claims
Unverified作者提交表单(Author Submission Form)主要收集作者个人层面的信息,如利益冲突、研究经验、是否愿意担任审稿人66% similarUnverifiedThe scoring rubric used by the author has been published at https://skill123.me/methodology, including the weights and the meaning of each dimension.63% similarUnverifiedARR's commitment mechanism allows authors to attach an author response when committing, in order to address reviewer comments or explain revisions.62% similarUnverifiedThe principle the author follows is: Muse proposes and executes, but the final decision and approval authority belongs to the human; any content must be confirmed by the author before being sent, published, or paid for.61% similarUnverifiedThe author publicly solicits feedback and contributions, particularly welcoming readers working in ML systems, inference, compilers, edge AI, or performance engineering to participate in co-building.60% similar
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