論壇

BEIJING, April 28, 2026  |  北京，2026年4月28日

Dr. Weihong Yan Presents Calligraphy Innovation Research at China Federation of Literary and Art Circles International Forum on Science and Art

闫伟红博士在中国文联科学与艺术国际论坛发表书法创新研究成果

 

PRESS RELEASE  ·  新闻通稿

World Association for Chinese Studies (USA)    美国世界中国学研究会

 

EVENT SUMMARY  /  活动概要

Forum: China Federation of Literary and Art Circles — International Forum on Science and Art

论坛：中国文联科学与艺术国际论坛

Venue: East Tower Multipurpose Hall, Guojin Tower, Beijing

地点：北京国际金融大厦东塔多功能厅

Date: April 28, 2026

日期：2026年4月28日

Speaker: Dr. Weihong Yan (闫伟红博士), Executive Director, World Association for Chinese Studies (USA)

发言人：闫伟红博士，美国世界中国学研究会执行会长

Presentation Title: Calligraphy Experiment: Word Innovation and Its Case Analysis

演讲题目与演讲语言：“中国汉字和书法实验：词的创新及其案例分析”；全英文演讲，现场同声翻译。

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On April 28, 2026, Dr. Weihong Yan, Executive Director and Senior Research Fellow of the World Association for Chinese Studies (USA), delivered a landmark eight-minute presentation at the China Federation of Literary and Art Circles (CFLAC) International Forum on Science and Art, held at the East Tower Multipurpose Hall of Guojin Tower, Beijing. His address — titled "Calligraphy Experiment: Word Innovation and Its Case Analysis" — introduced a groundbreaking research methodology at the intersection of calligraphic practice, structural analysis, and artificial intelligence theory.

2026年4月28日，美国世界中国学研究会执行会长、高级研究员闫伟红博士，在中国文联科学与艺术国际论坛上发表了题为《书法实验：词的创新及其案例分析》的重要学术演讲。此次论坛在北京国金大厦东塔多功能厅举行。这场历时八分钟的演讲，将书法实践、结构分析与人工智能理论融为一体，展示了具有开创意义的研究方法论。

 

A Field Without Words: The Origin of New Terminology / 无词可借：新术语的诞生

 

Dr. Yan opened his address with a deceptively simple observation: when a researcher enters a field never explored before, the first problem is not lack of data — it is lack of words. His research domain, Calligraphy and Contemporary Abstract Generation, has no prior scholarship, no established framework, and no existing vocabulary. This vacuum, he argued, is not an obstacle but an invitation — the experimental process itself becomes the mechanism of knowledge and concept production.

闫伟红博士以一个看似简单却深刻的问题开场：当研究者进入从未被探索过的领域，第一个问题不是缺少数据——而是缺少词语。他的研究领域——中国汉字和书法与当代性抽象生成——此前无人研究，没有现成框架，也没有专属词汇。他指出，这种真空状态绝非阻碍，反而一种契机——实验过程本身，即是知识与概念生成的机制。这种空白并非障碍，而是邀请——实验过程本身即成为知识生产的机制。

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"The experiment does not illustrate the concept — the experiment produces the concept."

「实验不是概念的插图——实验产生概念。」

 

The MCDET Framework:

SOD · MCLex · MCDET / MCDET 方法论框架

 

At the core of Dr. Yan's presentation was the introduction of three interlocking theoretical tools — each one emergent from experimental practice rather than imposed upon it.

闫伟红博士演讲的核心，是对三个相互交织的理论工具的介绍——每一个都是从实验实践中涌现，而非预先设定。

 

SOD (Salient Object Detection) detects and extracts structural units from a source character with independent generative potential. Dr. Yan positioned SOD not merely as a borrowed term from computer vision, but as the cognitive operation underlying more than three thousand years of Chinese character formation: ancient scribes had already practiced SOD when they detected the salient visual features of mountains, rivers, and eyes and extracted them as structural marks. The single-line stroke technique — 一笔画 — is SOD's fundamental expression in calligraphic practice.

SOD（显著对象检测）从汉字中识别并提取具有独立生成潜能的结构单元。闫博士指出，SOD 不仅仅是借用自网络计算机视觉的术语，而是支撑三千多年汉字形成传统的认知操作——古代书写者在将山、河、眼的显著视觉特征提取为结构性标记时，已在实践了SOD。一笔画技法是 SOD 在书法实践中最基础的表达。

 

MCLex (Multi-Conclusion Links Extraction) activates relational links between structural units, making the latent generative potential of a character visible. Each stroke, each component, each radical functions as a link — a relational unit capable of connecting to others. Dr. Yan drew a precise parallel to the AI concept of the token: while AI recognizes through statistical probability (a~b logic), MCLex recognizes through geometric and structural judgment — generating outputs of infinite and unknowable potential, what Dr. Yan calls the defamiliarization principle: a~z.

MCLex（多结论链接提取）激活结构单元之间的关系链接网络，使汉字潜在的生成性得以可见。每一笔画、每一部件、每一部首都作为 link 发挥功能。闫博士将其与 AI 中的 token 概念进行了精确类比：AI 通过统计概率识别（a～b 法则），而 MCLex 通过几何与结构判断识别——生成具有无限性与未知性的视觉输出，即闫博士所命名的陌生化法则：a～z。

 

MCDET (Medium-Determined Multi-Conclusion Deconstruction Experiment Theory) integrates deconstruction-différance, following Derrida, into a framework where medium is not a stylistic variable but the ontological determinant of the conclusion itself. Two works from the same source character through different media are not variations — they are categorically different phenomena.

MCDET（媒介决定的多结论解构实验理论）将德里达的解构延异理论整合进一个完整框架——媒介不是风格变量，而是决定结论本体范畴的根本因素。来自同一源字、经由不同媒介的两件作品，不是变体，而是范畴上不同的现象。

 

Three Case Analyses / 三个实验案例分析

 

Dr. Yan presented three experimental case analyses, each demonstrating a distinct dimension of the framework:

闫博士展示了三个实验案例分析，各自揭示了该方法论框架的不同维度：

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Case 1 — Six Script Forms of "Tiger" (虎) focused on SOD through the single-line stroke technique applied across oracle bone, bronze, seal, clerical, standard, and cursive scripts. The upper row presented the six historical character forms; the lower row revealed what SOD extracts — the structural skeleton of "tiger" freed from conventional readability.

案例一——「虎」六种字体形态：聚焦 SOD，通过一笔画技法贯穿甲骨文、金文、篆书、隶书、楷书、行草书六种字体。上排是六种历史字形；下排是 SOD 通过一笔画所揭示的：「虎」的结构骨架，从其惯常的可读性中解放出来。