Context is All You Need: GLAMs and LLMs

Ways of Viewing – East Asian Art, AI, Digital Art History

Kwok-leong Tang

Harvard University

2025-11-15

Intalling Software

• Cherry Studio: Homepage
• Cherry Studio is an open-source conversation client for AI integration.
• It provides two free AI models Qwen 3 8B and GLM 4.5 Air. Please note that these models are hosted by Chinese model providers. While they are useful for demonstration purposes, please be aware of data privacy considerations and use them at your own discretion.

Four components of AI-assisted Research (or Everything)

• Model (GPT, Claude, LLAMA, Qwen, DeepSeek)
• Prompt (use cases)
• Context (information)
• Tools (web search, interactions with APIs)

Nature and Limitations of Models

• Everything is PREDICTION.
• Every prediction is based on PROBABILITY!

Nature and Limitations of Models

Try the following prompt in Cherry Studio with Qwen3 8B:

What is your knowledge cutoff date? 
Who is the prime minister of Japan?

• Knowledge cutoff: October 2024
• Prime Minister: Fumio Kishida / Shigeru Ishiba (current: Sanae Takaichi)
• After training, a model’s parameters are frozen. Its built‑in knowledge would not change.

Nature and Limitation of Models

Try the following prompt in Cherry Studio with Qwen3 8B a couple of times:

Give a random number between 1 to 100.

• Do you find a 42 in your answer. Why?
• Because the number is the ultimate answer to life, the universe, and everything. You can read this article.
• Important

  Prediction and probability.

Context is the Solution

• Retrieve augment generation (RAG)
• Tool callings

What is my vision for the integration of humanities and AI in five years?

Every humanities researcher will be able to build their own AI-assisted tools for their unique research methods.

GLAMs will become an important part of the AI-assis research infrastructure which provide context.

A Major Obstacle to Adoption of Digital Tools and Methods in East Asian Studies prior to 2025: Optical Character Recognition (OCR)

• Traditional OCR struggled with CJK historical texts
• Poor accuracy with CJK characters
• Multiple calligraphic styles posed significant challenges

Washing Horses in a River (from CAEA Collection)

Three different styles of calligraphy. Image source.

Old OCR Result

如管4人工1馬汾1^^震專1-1-時檢奪 令？,之考噙皇^^‘幹卞卹肩螬野狄苳多 凊涑名‘樹連破闺會故牧&如鍺次^文玖 逸漣巧玉管囔長輝蟓1麩锊虼晻骨俗奇 碲爲—着相此也如讲雄姜^罕得孫場难 表木气！撫釔今人嚷大4 譽—嗜馎士柯X書3傅^壹闕’:’’、

數征青糙馬奉來不被鞅 本子秦用霞間救贲奚1*1

1公’翅鄞旅女箱嚐銬題

^{运’辜忍从七姑}^

紫题

Newly Emerging OCR Models

• Dots OCR from Rednote
• PaddleOCR-VL from PeddleOCR
• DeepSeek OCR from DeepSeek
• Chandra from Datalab

Demo on Kwok-leong’s Machine (2021 MacBook Pro)