journal-q1-polish

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Journal Q1 Polish

Q1期刊论文润色

Purpose: Final polish pass before submitting to Q1 journals (ISI/Scopus indexed). Ensures paper meets top-tier standards for notation consistency, language quality, and experimental rigor.

When to use: After paper draft is complete, before submission. NOT for initial writing — use

paper-writing

for that.

Links to:

```
paper-writing
```
— structure, sections, flow
```
technical-english-cs
```
— diction, terminology, IEEE/ACM style
```
experiment-tracking
```
— results tables, metrics format
```
internal-critique
```
— self-review checklist
```
publication-strategy
```
— venue selection, submission prep

用途： 向Q1期刊（ISI/Scopus收录）投稿前的最终润色环节。确保论文在符号一致性、语言质量和实验严谨性方面达到顶级期刊标准。

使用时机： 论文草稿完成后、投稿前使用。不适用于初稿写作——初稿写作请使用

paper-writing

工具。

关联工具：

```
paper-writing
```
— 结构、章节、行文逻辑
```
technical-english-cs
```
— 措辞、术语、IEEE/ACM格式
```
experiment-tracking
```
— 结果表格、指标格式
```
internal-critique
```
— 自我审查清单
```
publication-strategy
```
— 期刊选择、投稿准备

Step 1 — Notation & Complexity Sync (Paper ↔ Thesis)

步骤1 — 符号与复杂度同步（论文 ↔ 学位论文）

Paper phải dùng notation và complexity format giống thesis để tránh mâu thuẫn khi defend.

论文必须使用与学位论文一致的符号和复杂度格式，避免答辩时出现矛盾。

1.1 Notation Table

1.1 符号对照表

Tạo bảng notation mapping giữa paper và thesis:

Symbol	Paper	Thesis	Status
Learning rate	$\eta$	$\eta$	✅ Match
Batch size	$B$	$B$	✅ Match
Model params	$\theta$	$\theta$	✅ Match

Checklist:

Tất cả biến trong paper xuất hiện trong thesis notation table
Không có symbol conflict (cùng symbol, khác meaning)
Greek vs Latin letters consistent
Subscript/superscript convention thống nhất

创建论文与学位论文的符号映射表：

符号	论文	学位论文	状态
学习率	$\eta$	$\eta$	✅ 一致
批量大小	$B$	$B$	✅ 一致
模型参数	$\theta$	$\theta$	✅ 一致

检查清单：

论文中的所有变量均出现在学位论文的符号表中
无符号冲突（同一符号对应不同含义）
希腊字母与拉丁字母的使用保持一致
下标/上标的使用规则统一

1.2 Complexity Notation

1.2 复杂度符号

Q1 journals expect O(·) notation with explicit assumptions:

Time Complexity: O(T · N · d)
  T = number of rounds
  N = number of clients
  d = model dimension
  
Space Complexity: O(N · d)
  Per-client model storage

Rules:

Always state what each variable represents
Include amortized complexity if relevant
Compare with baseline complexity in the same format

Q1期刊要求O(·)符号需附带明确假设：

Time Complexity: O(T · N · d)
  T = number of rounds
  N = number of clients
  d = model dimension
  
Space Complexity: O(N · d)
  Per-client model storage

规则：

必须说明每个变量的含义
若相关，需包含摊销复杂度
使用相同格式与基线复杂度进行对比

1.3 Abstract ↔ Section 3.3 Complexity Sync

1.3 摘要 ↔ 3.3节复杂度同步

Critical for Q1: Complexity stated in abstract must exactly match the analysis in Section 3.3 (or equivalent methodology section). Mismatches are a common reviewer complaint.

Audit template:

Abstract claims: "O(T · N · d) time, O(N · d) space"
Section 3.3 states: "O(T · N · d) time, O(N · d) space"
Status: ✅ Match / ❌ Mismatch → fix: ___

Common mismatch patterns:

Abstract says "linear time" but Section 3.3 shows O(N²)
Abstract omits a factor (e.g., forgets communication rounds T)
Abstract uses different variable names than Section 3.3

Q1期刊关键要求： 摘要中陈述的复杂度必须与3.3节（或等效方法论章节）中的分析完全一致。不一致是审稿人常见的投诉点。

审计模板：

Abstract claims: "O(T · N · d) time, O(N · d) space"
Section 3.3 states: "O(T · N · d) time, O(N · d) space"
Status: ✅ Match / ❌ Mismatch → fix: ___

常见不一致模式：

摘要称“线性时间”但3.3节显示O(N²)
摘要遗漏某个因子（例如，忘记通信轮次T）
摘要使用的变量名称与3.3节不同

1.4 Sampling Ratio Notation Sync

1.4 采样率符号同步

When paper and thesis use different notation for the same concept, create explicit mapping:

Concept	Paper	Thesis	Unified Form
Effective sampling ratio	`\min(C.ratio, 75/N)`	`\min(s_{\text{config}}, T/N)`	`\min(r_{\text{max}}, S/N)`

Rule: Pick one form (prefer thesis notation if already established) and use consistently. Add a footnote in paper: "We use the notation from [thesis citation] for consistency."

当论文与学位论文对同一概念使用不同符号时，需创建明确的映射：

概念	论文	学位论文	统一格式
有效采样率	`\min(C.ratio, 75/N)`	`\min(s_{\text{config}}, T/N)`	`\min(r_{\text{max}}, S/N)`

规则： 选择一种格式（若学位论文已确立符号，优先使用）并保持一致。在论文中添加脚注：“为保持一致性，我们使用[学位论文引用]中的符号。”

1.5 Cross-Reference Audit

1.5 交叉引用审计

Every equation in paper has matching equation in thesis (or explicit note why different)
Algorithm pseudocode matches thesis Algorithm chapter
Complexity claims in paper abstract = complexity in thesis Chapter 3
Sampling ratio notation unified between paper and thesis

论文中的每个公式在学位论文中都有对应公式（或明确说明差异原因）
算法伪代码与学位论文的算法章节一致
论文摘要中的复杂度声明 = 学位论文第3章的复杂度
论文与学位论文的采样率符号统一

Step 2 — De-AI / De-translation Protocol

步骤2 — 去AI/去翻译痕迹规范

Q1 reviewers increasingly reject papers with AI-generated or machine-translated language. This step strips telltale signs.

Q1期刊审稿人越来越多地拒绝含有AI生成或机器翻译语言的论文。此步骤旨在去除这类明显痕迹。

2.1 AI Smell Detection (0-5 Score)

2.1 AI痕迹检测（0-5分）

Audit your paper for these AI-generated patterns:

Signal	Description	Example	Fix
Symmetrical structure	All bullets/paragraphs start with same word pattern	"Enhance X...", "Enhance Y...", "Enhance Z..."	Vary sentence openings
Abstract noun stacking	Chaining abstract nouns	"utilization of optimization strategies"	"using optimization"
Generic intro/outro	Vague opening/closing	"In today's rapidly evolving world..."	Start with specific problem
Excessive hedging	Too many qualifiers	"It could potentially be argued that..."	State directly: "X shows..."
Repetitive paraphrasing	Same idea restated differently	"This is important. This matters. This is significant."	State once, move on
Triple adjective stacking	3+ adjectives before noun	"novel comprehensive robust framework"	Pick one: "robust framework"
Passive voice overuse	>50% passive sentences	"It was found that..."	"We found..."
Connector overuse	furthermore, moreover, additionally every paragraph	"Furthermore, ... Moreover, ..."	Vary or restructure

Scoring:

0/5 — Natural human writing
1/5 — Minor AI痕迹, light edit needed
2/5 — Noticeable patterns, targeted fixes
3/5 — Multiple signals, significant revision
4/5 — Heavy AI smell, major rewrite
5/5 — Obviously AI-generated, total rewrite

Target: 0-1/5 for Q1 submission.

检查论文中是否存在以下AI生成模式：

信号	描述	示例	修改方法
对称结构	所有项目符号/段落以相同句式开头	"Enhance X...", "Enhance Y...", "Enhance Z..."	变换句子开头
抽象名词堆叠	连续使用抽象名词	"utilization of optimization strategies"	"using optimization"
通用引言/结论	模糊的开头/结尾	"In today's rapidly evolving world..."	以具体问题开篇
过度模糊表述	使用过多限定词	"It could potentially be argued that..."	直接陈述："X shows..."
重复 paraphrasing	同一观点用不同方式重复表述	"This is important. This matters. This is significant."	陈述一次后继续推进
三重形容词堆叠	名词前使用3个及以上形容词	"novel comprehensive robust framework"	选择一个："robust framework"
过度使用被动语态	被动句占比>50%	"It was found that..."	"We found..."
过度使用连接词	每段都使用furthermore, moreover, additionally	"Furthermore, ... Moreover, ..."	变换或重构句子

评分标准：

0/5 — 自然的人工写作
1/5 — 轻微AI痕迹，需轻度编辑
2/5 — 存在明显模式，需针对性修改
3/5 — 存在多种信号，需大幅修订
4/5 — 严重AI痕迹，需重写大部分内容
5/5 — 明显为AI生成，需完全重写

目标：Q1投稿需达到0-1/5分。

2.2 Hype Words Blacklist

2.2 夸大词汇黑名单

BAN these words/phrases entirely:

Banned	Replace with
delve into	examine, investigate, explore
leverage	use, apply, employ
robust	reliable, stable, consistent
cutting-edge	current, recent, state-of-the-art
novel	(just delete — let the work speak)
groundbreaking	(delete)
paradigm	approach, framework, method
landscape	field, domain, area
tapestry	(delete)
meticulous	careful, thorough
furthermore	(use "Additionally" or restructure sentence)
moreover	(same)
in conclusion	(delete — just end the section)
it is worth noting	(delete — if worth noting, just state it)
comprehensive	complete, full, extensive
innovative	(delete or specify what's new)
significant improvement	improvement of X% (be specific)
state-of-the-art	current best, recent methods (cite them)
demonstrates	shows, indicates, confirms
facilitates	enables, allows, supports
enhances	improves, increases
utilizing	using
aforementioned	(delete — restructure)
subsequently	then, next, after
preliminary	initial, early

完全禁用以下词汇/短语：

禁用词汇	替代表达
delve into	examine, investigate, explore
leverage	use, apply, employ
robust	reliable, stable, consistent
cutting-edge	current, recent, state-of-the-art
novel	(直接删除——让成果自己说话)
groundbreaking	(删除)
paradigm	approach, framework, method
landscape	field, domain, area
tapestry	(删除)
meticulous	careful, thorough
furthermore	(使用"Additionally"或重构句子)
moreover	(同上)
in conclusion	(删除——直接结束章节)
it is worth noting	(删除——若值得提及，直接陈述即可)
comprehensive	complete, full, extensive
innovative	(删除或具体说明创新点)
significant improvement	improvement of X%（需具体）
state-of-the-art	current best, recent methods（需引用）
demonstrates	shows, indicates, confirms
facilitates	enables, allows, supports
enhances	improves, increases
utilizing	using
aforementioned	(删除——重构句子)
subsequently	then, next, after
preliminary	initial, early

2.2 Passive → Active Voice

2.3 被动语态转主动语态

Q1 journals prefer active voice. Scan for passive patterns:

Passive (bad):

The model was trained on the dataset.
Experiments were conducted to evaluate performance.
It was found that the method outperforms baselines.

Active (good):

We trained the model on the dataset.
We evaluated performance through experiments.
The method outperforms baselines.

Exception: Methods section can use passive for standard procedures ("The dataset was split into 80/20 train/test").

Q1期刊偏好主动语态。扫描被动语态模式：

被动语态（不佳）：

The model was trained on the dataset.
Experiments were conducted to evaluate performance.
It was found that the method outperforms baselines.

主动语态（良好）：

We trained the model on the dataset.
We evaluated performance through experiments.
The method outperforms baselines.

例外： 方法章节中针对标准流程可使用被动语态（例如"The dataset was split into 80/20 train/test"）。

2.4 Quantify Hype with Experimental Data

2.4 用实验数据量化夸大表述

Rule: When encountering hype words, replace with specific numbers from your results.

Hype phrase	Bad (vague)	Good (data-driven)
"extremely fast"	"The method is extremely fast"	"The method converges in 43 rounds vs. 67 for FedAvg (35.8% reduction)"
"significantly better"	"Our method performs significantly better"	"Our method achieves 94.3% accuracy, outperforming the best baseline by 2.2 percentage points (p < 0.001)"
"absolutely robust"	"The approach is absolutely robust to noise"	"Accuracy degrades by only 0.8% when noise increases from 0% to 30%"
"vastly superior"	"Our framework is vastly superior"	"Our framework reduces communication cost by 35% while maintaining comparable accuracy"
"extremely efficient"	"The algorithm is extremely efficient"	"The algorithm runs in O(N log N) time, 2.3× faster than the O(N²) baseline"

Workflow:

Search document for: extremely, vastly, absolutely, incredibly, remarkably, substantially, considerably
For each hit, locate the corresponding result in your experiments
Replace with: metric + value + comparison/baseline

规则： 遇到夸大词汇时，替换为结果中的具体数据。

夸大表述	不佳（模糊）	良好（数据驱动）
"extremely fast"	"The method is extremely fast"	"The method converges in 43 rounds vs. 67 for FedAvg (35.8% reduction)"
"significantly better"	"Our method performs significantly better"	"Our method achieves 94.3% accuracy, outperforming the best baseline by 2.2 percentage points (p < 0.001)"
"absolutely robust"	"The approach is absolutely robust to noise"	"Accuracy degrades by only 0.8% when noise increases from 0% to 30%"
"vastly superior"	"Our framework is vastly superior"	"Our framework reduces communication cost by 35% while maintaining comparable accuracy"
"extremely efficient"	"The algorithm is extremely efficient"	"The algorithm runs in O(N log N) time, 2.3× faster than the O(N²) baseline"

流程：

在文档中搜索：extremely, vastly, absolutely, incredibly, remarkably, substantially, considerably
针对每个匹配项，找到实验中对应的结果
替换为：指标 + 数值 + 对比/基线

2.5 De-translation Patterns

2.5 去翻译痕迹模式

If paper was translated from Vietnamese:

Vietnamese structure	English fix
"The method has the ability to..."	"The method can..."
"In order to..."	"To..."
"Due to the fact that..."	"Because..."
"At the present time"	"Currently" / "Now"
"In the event that"	"If"
"Despite the fact that"	"Although" / "Despite"
"On a daily basis"	"Daily"
"Has the potential to"	"Can" / "May"

若论文由越南语翻译为英文，需修正以下常见翻译痕迹：

越南语式英文结构	标准英文修正
"The method has the ability to..."	"The method can..."
"In order to..."	"To..."
"Due to the fact that..."	"Because..."
"At the present time"	"Currently" / "Now"
"In the event that"	"If"
"Despite the fact that"	"Although" / "Despite"
"On a daily basis"	"Daily"
"Has the potential to"	"Can" / "May"

2.6 Sentence Length Audit

2.6 句子长度审计

Target: 15-25 words per sentence
Hard max: 35 words (split if longer)
Check: any paragraph with 3+ consecutive sentences > 25 words → rewrite

目标：每句15-25词
上限：35词（超过则拆分）
检查：若某段落存在3句及以上连续超过25词的句子 → 重写

Step 3 — Q1 Results Table Standard

步骤3 — Q1期刊结果表格标准

Q1 journals expect rigorous experimental reporting. This is the #1 rejection reason for ML/AI papers.

Q1期刊要求严谨的实验报告。这是ML/AI论文被拒的首要原因。

3.1 Mandatory Columns

3.1 必填列

Column	Required	Notes
Method	✅	Full name + citation
Metric(s)	✅	Primary metric bolded
Mean	✅	Arithmetic mean
Std Dev	✅	MANDATORY for ablation studies
# Seeds	✅	Minimum 3, recommend 5
p-value	⚠️	Required if claiming "significant improvement"

列名	是否必填	说明
方法	✅	全称 + 引用
指标	✅	主要指标加粗
均值	✅	算术平均值
标准差	✅	消融研究必填
种子数	✅	最少3个，推荐5个
p值	⚠️	若声称“显著提升”则必填

3.2 Ablation Study Format

3.2 消融研究格式

⚠️ CRITICAL: Every cell in an ablation table must include mean ± standard deviation. No exceptions.

WRONG (rejection risk):

| Method    | Accuracy |
|-----------|----------|
| Baseline  | 85.2     |
| + Module A| 87.1     |
| + Module B| 88.3     |

RIGHT (Q1 standard):

| Method     | Accuracy       | # Seeds | p-value  |
|------------|----------------|---------|----------|
| Baseline   | 85.2 ± 0.3     | 5       | —        |
| + Module A | 87.1 ± 0.4     | 5       | 0.002*   |
| + Module B | 88.3 ± 0.2     | 5       | <0.001*  |

* Statistically significant (paired t-test, α=0.05)

Rule: If a result cell shows only a single number (e.g.,

85.2

), it is incomplete. Every value must be

mean ± std

format.

⚠️ 关键要求： 消融表格中的每个单元格必须包含均值±标准差。无例外。

错误示例（存在被拒风险）：

| Method    | Accuracy |
|-----------|----------|
| Baseline  | 85.2     |
| + Module A| 87.1     |
| + Module B| 88.3     |

正确示例（Q1标准）：

| Method     | Accuracy       | # Seeds | p-value  |
|------------|----------------|---------|----------|
| Baseline   | 85.2 ± 0.3     | 5       | —        |
| + Module A | 87.1 ± 0.4     | 5       | 0.002*   |
| + Module B | 88.3 ± 0.2     | 5       | <0.001*  |

* Statistically significant (paired t-test, α=0.05)

规则： 若结果单元格仅显示单个数值（例如

85.2

），则表格不完整。所有数值必须采用

均值 ± 标准差

格式。

3.3 Seed Count Justification

3.3 种子数说明

Include in experimental setup:

We report mean ± standard deviation over N independent runs with
different random seeds. We use [5/10/30] seeds to ensure reliable
statistical inference and reproducibility of our results.

Seed count guidelines:

Domain	Minimum Seeds	Justification
Deep Learning (deterministic)	3-5	Low variance, GPU determinism
Deep Learning (stochastic)	5-10	Moderate variance
Federated Learning	5-10	Client sampling variance
Metaheuristic / Evolutionary	30	Central Limit Theorem (n ≥ 30 for normality)
Reinforcement Learning	10-30	High variance, environment stochasticity

Why CLT matters for n ≥ 30:

Sampling distribution of mean approximates normality regardless of population distribution
Enables parametric tests (t-test, ANOVA) even for non-normal results
Standard expectation in empirical research methodology

Template:

We report mean ± standard deviation over [N] independent runs
(seed ∈ {42, 123, 456, ...}). [N] seeds ensure [reliable statistical
inference / CLT normality / reproducibility] per standard empirical
methodology.

在实验设置部分添加以下内容：

We report mean ± standard deviation over N independent runs with
different random seeds. We use [5/10/30] seeds to ensure reliable
statistical inference and reproducibility of our results.

种子数指南：

领域	最少种子数	说明
深度学习（确定性）	3-5	低方差，GPU确定性
深度学习（随机性）	5-10	中等方差
联邦学习	5-10	客户端采样方差
元启发式/进化算法	30	中心极限定理（n≥30时近似正态分布）
强化学习	10-30	高方差，环境随机性

为何n≥30时中心极限定理重要：

均值的抽样分布近似正态分布，与总体分布无关
即使结果非正态，也能使用参数检验（t检验、方差分析）
实证研究方法论中的标准要求

模板：

We report mean ± standard deviation over [N] independent runs
(seed ∈ {42, 123, 456, ...}). [N] seeds ensure [reliable statistical
inference / CLT normality / reproducibility] per standard empirical
methodology.

3.4 Statistical Tests

3.4 统计检验

Claim	Required Test
"outperforms" / "better than"	Paired t-test or Wilcoxon signed-rank
"comparable" / "similar"	Equivalence test or confidence interval overlap
"robust to hyperparameter"	Sensitivity analysis table

声明	所需检验方法
"优于" / "比……更好"	配对t检验或Wilcoxon符号秩检验
"相当" / "相似"	等效性检验或置信区间重叠分析
"对超参数鲁棒"	敏感性分析表

3.5 Results Table Checklist

3.5 结果表格检查清单

All cells in ablation study show
```
mean ± std
```
(not just main results table)
Seed count stated for each experiment (minimum 30 for metaheuristics per Đurasević & Jakobović [2023])
Statistical significance marked with asterisk + footnote
Best result bolded, second-best underlined
Baseline results from original paper cited, not re-implemented (unless stated)
Hardware spec mentioned (GPU type, RAM) for reproducibility
Runtime/latency comparison if claiming efficiency

所有单元格（不仅是主结果表）的消融研究均采用
```
均值 ± 标准差
```
格式
每个实验均说明种子数（元启发式算法需至少30个，参考Đurasević & Jakobović [2023]）
统计显著性用星号标注并添加脚注
最佳结果加粗，次佳结果下划线标注
基线结果引用原论文，而非重新实现（除非明确说明）
提及硬件规格（GPU型号、内存）以保证可复现性
若声称高效性，需包含运行时间/延迟对比

Final Polish Checklist

最终润色检查清单

From

internal-critique

来自

internal-critique

Self-review using internal-critique checklist
Address all "fatal flaw" items before submission

使用internal-critique清单进行自我审查
投稿前解决所有“致命缺陷”项

From

technical-english-cs

来自

technical-english-cs

Diction matches IEEE/ACM standards
No Vietnamese-English translation artifacts

措辞符合IEEE/ACM标准
无越英翻译痕迹

From

paper-writing

来自

paper-writing

Section structure follows target venue template
Abstract within word limit
References formatted correctly

章节结构遵循目标期刊模板
摘要符合字数限制
参考文献格式正确

From

publication-strategy

来自

publication-strategy

Selected venue matches paper scope
Checked recent acceptance rate
Reviewed 2-3 recent papers from target venue for style

所选期刊与论文范围匹配
查看过近期录用率
参考过目标期刊的2-3篇近期论文以匹配风格

Integration Flow

整合流程

paper-writing (draft complete)
    ↓
journal-q1-polish (this skill)
    ├── Step 1: notation-sync
    ├── Step 2: de-ai-protocol
    └── Step 3: q1-results-standard
    ↓
internal-critique (final review)
    ↓
publication-strategy (venue selection + submission)

paper-writing (draft complete)
    ↓
journal-q1-polish (this skill)
    ├── Step 1: notation-sync
    ├── Step 2: de-ai-protocol
    └── Step 3: q1-results-standard
    ↓
internal-critique (final review)
    ↓
publication-strategy (venue selection + submission)

journal-q1-polish

Original

Translation

Journal Q1 Polish

Q1期刊论文润色

Step 1 — Notation & Complexity Sync (Paper ↔ Thesis)

步骤1 — 符号与复杂度同步（论文 ↔ 学位论文）

1.1 Notation Table

1.1 符号对照表

1.2 Complexity Notation

1.2 复杂度符号

1.3 Abstract ↔ Section 3.3 Complexity Sync

1.3 摘要 ↔ 3.3节复杂度同步

1.4 Sampling Ratio Notation Sync

1.4 采样率符号同步

1.5 Cross-Reference Audit

1.5 交叉引用审计

Step 2 — De-AI / De-translation Protocol

步骤2 — 去AI/去翻译痕迹规范

2.1 AI Smell Detection (0-5 Score)

2.1 AI痕迹检测（0-5分）

2.2 Hype Words Blacklist

2.2 夸大词汇黑名单

2.2 Passive → Active Voice

2.3 被动语态转主动语态

2.4 Quantify Hype with Experimental Data

2.4 用实验数据量化夸大表述

2.5 De-translation Patterns

2.5 去翻译痕迹模式

2.6 Sentence Length Audit

2.6 句子长度审计

Step 3 — Q1 Results Table Standard

步骤3 — Q1期刊结果表格标准

3.1 Mandatory Columns

3.1 必填列

3.2 Ablation Study Format

3.2 消融研究格式

3.3 Seed Count Justification

3.3 种子数说明

3.4 Statistical Tests

3.4 统计检验

3.5 Results Table Checklist

3.5 结果表格检查清单

Final Polish Checklist

最终润色检查清单

From internal-critique

来自internal-critique

From technical-english-cs

来自technical-english-cs

From paper-writing

来自paper-writing

From publication-strategy

来自publication-strategy

Integration Flow

整合流程

From
`internal-critique`

来自
`internal-critique`

From
`technical-english-cs`

来自
`technical-english-cs`

From
`paper-writing`

来自
`paper-writing`

From
`publication-strategy`

来自
`publication-strategy`