简体中文 | English
An academic paper written using the CSF minimal version (
context.mdtemplate). 17 dialogue logs + bilingual submissions + collaboration memory file, documenting the full process from “discussing the skeleton” to “arXiv submission” to “data analysis and revision” to “IEEE Software submission.”
“This Paper Was Written by AI” is an academic paper (under submission). Its subject is CSF itself — semantic drift in long-range human-AI collaboration — introducing two core concepts: “Index Sickness” and the “Pang Principle.”
The writing process is a demonstration of the paper’s thesis: all text was generated by AI collaborators, with the Owner providing only directional judgment. The collaboration used the context.md template from csf-minimal — at the start of each session, the AI reads it to reconstruct project state; at the end, it updates it to maintain continuity. This file itself is a record and evidence of the collaboration.
| File | Description |
|---|---|
| context.md | Collaboration memory file used during writing (csf-minimal template instance) |
| arxiv_submission_zh.md | Chinese arXiv submission (primary, finalized) |
| arxiv_submission_en.md | English arXiv submission (v1.6, synced with Chinese) |
| dlog/ | 17 raw dialogue logs + analysis scripts + submission notes |
| ieee-software/ | IEEE Software submission materials (cover letter, submission, statement) |
| closing-remarks-en.md | Screenshots of “Closing Remarks” from dlog_17 — the paper’s most powerful external proof |
| File | Core Event |
|---|---|
| dlog_1 | First skeleton discussion — narrative arc, core concepts, target venue |
| dlog_2 | Initial material collection — literature search, case material compilation |
| dlog_3 | First writing attempt — messy structure but solid material |
| dlog_4 | Switched to a more stable AI persona |
| dlog_5 | Chrome + Gemini assisted literature review |
| dlog_6 | Initial integration of review into paper |
| dlog_7 | First polishing pass — language, logic, citations |
| dlog_8 | Translation + English version launch |
| dlog_9 | Argument structure revision — introduction reorganization, contribution reordering |
| dlog_10 | Global review + simulated harsh reviewer role-play (DeepSeek) |
| dlog_11 | Further Chinese revisions |
| dlog_12 | English finalization + arXiv upload |
| dlog_13 | Systematic data mining — correction density, context growth rate, two-round simplification comparison |
| dlog_14 | Incorporating data findings into the paper (v1.5 → v1.6) |
| dlog_15 | Simulated harsh reviewer feedback + Owner’s point-by-point response |
| dlog_16 | arXiv update upload (v1.6 finalized) |
| dlog_17 | IEEE Software submission — formatting, cover letter, final submission → 📜 Closing Remarks |
| dlog_paper1_issues | Issue tracking log (14 issues with disposition) |
| data-analysis/ | Analysis scripts (Python), statistical results, paper enhancement recommendations |
| notes | Submission target notes (IEEE Software / ICSE, etc.) |
The paper was written using the basic pattern from csf-minimal:
context.md as collaboration memory: read at session start, updated at session end. Across 17 sessions, the AI never needed the Owner to re-explain background.No multi-agent simulation, no physical isolation, no other advanced mechanisms. Just a context.md template + normal dialogue collaboration. The paper’s quality came from this minimal setup.
The raw dialogue logs retain Copilot tool invocation traces (Read, Searched, Created lines) and some AI intermediate reasoning output. These are uncleaned because they are themselves verifiable evidence — a third party can verify whether cases and arguments cited in the paper indeed originate from the corresponding session records.
If you just want to understand the process, this page is enough. If you want to verify the evidence, dig into the dlog raw files.