TWBG_Materials/文档润色流和知识库构建流/claude-scholar-upstream/skills/ml-paper-writing/references/knowledge/writing-techniques.md

Writing Techniques and Patterns

This file contains actionable sentence patterns, transition phrases, and writing techniques extracted from successful ML conference papers.

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Transition Phrases

Literature Review Transitions

Source: Various NeurIPS/ICML papers

Introducing Problems:

• "However, these methods suffer from [limitation]."
• "Despite recent progress, [challenge] remains unsolved."
• "While existing approaches address [aspect], they struggle with [issue]."

Presenting Solutions:

• "To address this, we propose..."
• "We overcome this limitation by..."
• "Our key insight is that..."

Connecting to Related Work:

• "Building on [prior work], we extend..."
• "Unlike approaches that [method], we instead..."
• "Following the success of [paper], we apply..."

Methods Section Transitions

Source: "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)

Describing Components:

• "Our model consists of two main components: [A] and [B]."
• "We divide our approach into [N] stages: [list]."

Explaining Rationale:

• "We choose this architecture because..."
• "This formulation allows us to..."
• "Motivated by [intuition], we design..."

Results Section Transitions

Source: "Attention Is All You Need", NeurIPS (2017)

Presenting Findings:

• "Our method achieves [result], outperforming baselines by [margin]."
• "As shown in Table 1, our approach..."
• "Figure 2 demonstrates that..."

Analyzing Results:

• "These results suggest that [insight]."
• "Notably, we observe that..."
• "This improvement indicates that..."

Discussion Transitions

Source: "Language Models are Few-Shot Learners", GPT-3 (2020)

Interpreting Findings:

• "These findings reveal that..."
• "This performance gap suggests that..."
• "The strong correlation between...indicates..."

Connecting to Broader Context:

• "Beyond the specific task, our results imply..."
• "This has important implications for..."

Acknowledging Limitations:

• "It is important to note that our study is limited to..."
• "While these results are promising, several questions remain..."

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Sentence Patterns

Claim Presentation

Source: "Attention Is All You Need", NeurIPS (2017)

Strong Claims:

• "We show that [approach] achieves [result]."
• "We demonstrate that [method] outperforms..."
• "We prove that [technique] converges to..."

Nuanced Claims:

• "Our results suggest that [factor] contributes to..."
• "We observe that [phenomenon] emerges when..."
• "Experiments indicate that [approach] is particularly effective for..."

Technical Description

Source: "Adam: A Method for Stochastic Optimization", ICLR (2015)

Algorithm Description:

• "Formally, we optimize [objective] using [method]."
• "The update rule for [parameter] is given by..."
• "We modify the standard [approach] by..."

Implementation Details:

• "In practice, we implement [feature] as..."
• "For computational efficiency, we approximate..."
• "We initialize [parameters] using..."

Results Presentation

Source: "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)

Quantitative Results:

• "Our model achieves [score] (±[std]), improving over..."
• "On [dataset], we obtain [result], compared to..."
• "We observe a [percentage]% improvement over baselines."

Statistical Reporting:

• "Results are averaged over N runs with different seeds."
• "Standard deviations are shown in parentheses."
• "The improvement is statistically significant (p<0.01)."

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Clarity Techniques

Active Voice Usage

Source: Various well-written papers

Passive (avoid):

• "The model was trained using..."
• "Experiments were conducted on..."

Active (prefer):

• "We trained the model using..."
• "We conducted experiments on..."

Guideline: Use active voice for actions you performed. Use passive for general facts or when the actor is unclear.

Specificity Over Generality

Source: "Attention Is All You Need", NeurIPS (2017)

Vague (avoid):

• "This approach improves performance."
• "The method learns good representations."

Specific (prefer):

• "This approach improves accuracy by 15%."
• "The method learns representations that transfer to downstream tasks."

Guideline: Be quantitative whenever possible. Use specific numbers and metrics.

Signposting

Source: "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)

Section Openings:

• "We now describe our model architecture."
• "We evaluate on three tasks: [list]."
• "The results suggest three key insights:"

Internal Structure:

• "First, we [action]. Next, we [action]. Finally, we [action]."
• "Our approach has three stages: [A], [B], and [C]."

Guideline: Use explicit signposting to help tired reviewers follow your paper.

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Common Phrase Templates

Opening Abstract

Good Examples:

• "We introduce [method], a novel approach for [task]."
• "We present [method], which achieves [result] by [mechanism]."
• "We propose [framework] to address [challenge]."

Avoid:

• "In this paper, we study..." (generic)
• "Large language models have..." (overused opening)

Introducing Related Work

Good Examples:

• "Recent work has shown promise in [area] [refs]."
• "Several approaches have been proposed for [task] [refs]."
• "The standard approach to [problem] is [method] [refs]."

Describing Experiments

Good Examples:

• "We evaluate on [datasets], comparing against [baselines]."
• "We conduct ablation studies to validate [component]."
• "To verify [claim], we experiment with [variations]."

Presenting Results

Good Examples:

• "Table 1 shows that our method outperforms all baselines."
• "As shown in Figure 3, performance improves as [factor] increases."
• "Our method achieves state-of-the-art on [task/metric]."

Discussing Limitations

Good Examples:

• "Our approach has limitations: [constraint]."
• "We note that our method is currently restricted to [condition]."
• "A key limitation is [issue], which we leave for future work."

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Writing Principles

From Top Papers

Clarity First:

• "Make it easy for reviewers to understand your contribution."
• "Use concrete examples and specific language."
• "Avoid vague or ambiguous statements."

Rigorous Presentation:

• "Provide enough detail for reproduction."
• "Include error bars and statistical tests."
• "Show negative results when relevant."

Storytelling:

• "Your paper tells a story: problem → approach → solution → impact."
• "Make the narrative clear in the introduction."
• "Each section should advance the story."

Honesty:

• "Acknowledge limitations explicitly."
• "Don't overclaim results."
• "Trust reviewers to appreciate honesty."

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Notes

• Adapt patterns: These templates can and should be adapted to your specific context
• Venue matters: Some venues prefer certain styles (check venue-specific guides)
• Consistency: Use consistent terminology throughout
• Tone: Maintain professional, objective tone
• Length: Keep transitions concise; don't over-explain

Attribution: All patterns extracted from analyzed papers with source citations for traceability.

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"Surprisingly" Findings: Multi-Level Reporting Pattern

Source: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, ECCV 2022), "Mean Flows" (2025)

Paper Type: Design simplification, unexpected findings

The Three-Level "Surprisingly" Pattern

Level 1: Basic Surprise (Abstract/Opening)

Pattern:

Surprisingly, we observe: (i) [simple sufficient without common practice]
and (ii) [simple sufficient without common practice]

Example (ViTDet Abstract):

Surprisingly, we observe: (i) it is sufficient to build a simple feature
pyramid from a single-scale feature map (without the common FPN design) and
(ii) it is sufficient to use window attention (without shifting) aided with
very few cross-window propagation blocks.

Key Techniques:

• Structured list: Use (i) and (ii) to separate findings
• "sufficient": Scientific phrasing (not "optimal")
• "without [common practice]": Negative differentiation

Level 2: Competitive Surprise (Introduction)

Pattern:

More surprisingly, under some circumstances, our [method] can compete
with the leading [competitors].

Example (ViTDet Introduction):

More surprisingly, under some circumstances, our plain-backbone detector,
named ViTDet, can compete with the leading hierarchical-backbone detectors
(e.g., Swin, MViT).

Key Techniques:

• "More surprisingly": Progressive emphasis
• "under some circumstances": Measured claim
• "can compete with": Not "beat", competitive
• Name competitors: Specific (Swin, MViT)

Level 3: Superiority Surprise (Results)

Pattern:

With [specific condition], our [method] can outperform the [competitors]
that use [stronger condition]. The gains are more prominent for [condition].

Example:

With Masked Autoencoder (MAE) pre-training, our plain-backbone detector can
outperform the hierarchical counterparts that are pre-trained on ImageNet-1K/21K
with supervision (Figure 3). The gains are more prominent for larger model sizes.

Key Techniques:

• Specific conditions compared: MAE vs ImageNet supervised
• "outperform": Stronger claim here (qualified by conditions)
• "The gains are more prominent for...": Pattern observation

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"Surprisingly" Variants

"Interestingly" - Pattern Observation + Explanation

Pattern:

Interestingly, [observation]. This is in line with the observation in [paper]
that [their finding]. [Additional explanation].

Example (ViTDet):

Interestingly, performing propagation in the last 4 blocks is nearly as
good as even placement. This is in line with the observation in ViT [14]
that ViT has longer attention distance in later blocks and is more localized
in earlier ones.

Use when: You have literature support for your observation

"Notably" - Important Detail

Pattern:

Notably, [counter-intuitive result or impressive number].

Examples:

• "Notably, even embedding only the interval t−r yields reasonable results."
• "Notably, our method is self-contained and trained entirely from scratch."

Use when: Emphasizing importance or counter-intuitive finding

"It is worth noting that" - Caveat/Clarification

Pattern:

It is worth noting that [technical caveat or clarification].

Examples:

• "It is worth noting that even when the conditional flows are designed to be straight ('rectified'), the marginal velocity field typically induces a curved trajectory."
• "It is worth noting that the 3.34× memory (49G) is estimated as if the same training implementation could be used, which is not practical and requires special memory optimization."

Use when: Preventing misunderstanding or clarifying technical details

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When to Use "Surprisingly"

DO use:

• When finding genuinely contradicts common practice
• When simple solution works as well as complex one
• When you have explanation (literature, hypothesis, theory)
• With measured claims ("under some circumstances", "can compete")
• With "sufficient" not "optimal"

DON'T use:

• For incremental improvements (use "additionally" instead)
• Without explanation/justification
• Overgeneralizing ("always", "proves")
• For expected results

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Ablation Study Writing Techniques

Source: Kaiming He papers (ViTDet, MeanFlows, MoCo v2)

Table Design: Incremental Progression

Pattern:

Table X: [Component] Ablation
┌──────────────────────────────────────────┐
│ no [component]        | AP     | Δ       │
│ (a) [common variant]  | AP     | +X.X    │
│ (b) [another variant] | AP     | +Y.Y    │
│ (c) ours: simple      | AP     | +Z.Z ✓  │
└──────────────────────────────────────────┘

Example (ViTDet Table 1):

pyramid design              APbox   APmask
─────────────────────────────────────────
no feature pyramid          47.8    42.5
(a) FPN, 4-stage           50.3    44.9
(b) FPN, last-map          50.9    45.3
(c) simple feature pyramid  51.2    45.5

Techniques:

• Baseline: "no [X]" shows it's needed
• (a), (b), (c): Progressive variations
• Δ标注: (+2.5) - Show incremental gains
• Correspondence: "The entries (a-c) correspond to Figure X (a-c)"
• Conclusion: "our simple pyramid is sufficient"

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Destructive Ablation: Proving Necessity

Pattern:

We conduct a destructive comparison in which [wrong choice] is intentionally
performed. Meaningful results are achieved only when [correct choice].

Example (MeanFlows Table 1b):

In Tab. 1b, we conduct a destructive comparison in which incorrect JVP
computation is intentionally performed.

jvp tangent          FID, 1-NFE
(v, 0, 1) [correct]   61.06
(v, 0, 0) [wrong]     268.06
(v, 1, 0) [wrong]     329.22
(v, 1, 1) [wrong]     137.96

It shows that meaningful results are achieved only when the JVP computation
is correct.

Use when: You need to prove a design choice is necessary (not just optional)

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Ablation Narrative: Observation → Explanation

Pattern 1: Observation + Literature Support

We observe that [observation]. This is consistent with the observation in
[paper] that [their finding].

Pattern 2: Observation + Hypothesis

We hypothesize that this is because [reason 1] and also because [reason 2].

Pattern 3: Observation + Theory

[Observation]. This indicates that [theoretical explanation].

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Theory-Driven Paper Keywords

Source: Kaiming He et al., "Mean Flows for One-step Generative Modeling" (2025)

Naturalness Keywords (use to describe your theory)

• "naturally" - "This naturally leads to..."
• "intrinsic" - "intrinsic relation between..."
• "well-defined" - "well-defined problem"
• "principled" - "principled basis for..."
• "first principles" - "from first principles"
• "solely originated from" - "solely from definition"

Independence Keywords

• "does not depend on" - Theory independence from implementation
• "independent of" - Independent of specific choices
• "self-contained" - System independence
• "from scratch" - No external dependencies
• "without any X" - Negative list (what you don't need)

Differentiation Keywords

• "in contrast to" - Conceptual contrast
• "unlike" - Direct comparison
• "typically" - "typically modeled" (their approach)
• "prior works typically rely on" - Their limitation
• "imposed as" - Artificial constraint (theirs)

Avoid (Too Promotional)

• ❌ "revolutionary" - Let others say it
• ❌ "breakthrough" - Overused
• ❌ "completely eliminates" - Too absolute
• ✅ "significantly outperforms" - Strong but measured
• ✅ "substantial improvement" - Professional

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Design Simplification Paper Keywords

Source: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, 2022)

Philosophy Keywords

• "minimal" - "minimal adaptations"
• "sufficient" - "is sufficient to" (not "optimal")
• "simple" - "simple feature pyramid"
• "plain" - "plain backbone"
• "decouple" - "decouple pre-training from fine-tuning"
• "independence" - "independence of upstream vs downstream"

Direction Keywords

• "pursue a different direction" - Clear positioning
• "in contrast to" - Differentiation
• "abandons" - What you give up (respectfully)
• "enables" - What your approach allows

Measured Claim Keywords

• "under some circumstances" - Not always
• "can compete with" - Competitive, not dominant
• "more prominent for" - When effect is stronger
• "is sufficient" - Necessary, not maximal

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Updated: 何凯明的写作技巧

来源: 分析了何凯明的 11 篇代表性论文（扩展分析，包括 MeanFlows、ViTDet、MAR 等） 添加时间: 2026-01-26

扩展内容包括：

• "Surprisingly" 发现的多层次报告模式
• Ablation Study 的增量式和破坏性实验设计
• 理论驱动型论文的关键词策略
• 设计简化型论文的关键词策略

句子结构偏好

主动语态优先 (被动语态仅 9.3%) 何凯明偏好使用主动、直接的陈述：

✅ 推荐 (何凯明的风格):

• "We present a framework for [task]"
• "Our method achieves [result]"
• "This formulation enables [benefit]"

❌ 避免:

• "A framework is presented for [task]"
• "Results are achieved by our method"

贡献表达方式

何凯明常用的贡献表达模式：

模式 1: 直接陈述

We propose [method] that [feature].
We demonstrate [result] on [dataset].

模式 2: 对比强调

Unlike [previous work], our approach [difference].
This leads to [improvement] in [metric].

模式 3: 问题-解决方案

[Challenge] remains difficult. We address this by [solution].

技术术语使用

何凯明论文中的高频术语组合：

术语类别	常用术语
网络架构	deep neural networks, convolutional, residual, activation
训练过程	training, validation, optimization, convergence
性能评估	outperforms, achieves, improves, surpasses
方法定位	state-of-the-art, baseline, framework, algorithm
所有权	our method, our approach, our framework

过渡短语

何凯明论文中常用的过渡短语（按频率排序）：

1. however - 用于对比不同观点
2. in addition/additionally - 补充信息
3. furthermore - 递进说明
4. therefore/thus - 得出结论
5. specifically - 举例说明
6. conversely - 对比说明

数值结果呈现

何凯明在呈现数值结果时的模式：

精确性优先:

Our method achieves 76.4% accuracy (Table X).
This represents a 28% relative improvement.

对比式呈现:

Compared to baseline (73.2%), our method (76.4%) improves
by 3.2 percentage points.

强调意义:

This result won the 1st place in [competition/task].

图表引用模式

何凯明引用图表的标准格式：

图表引入:

• "Fig. X shows [现象]"
• "Table Y summarizes [结果]"
• "As shown in Fig. Z, [结论]"

图表描述:

• "The solid line denotes [条件 A], the dashed line [条件 B]"
• "The blue curve shows [指标], while the red curve shows [指标]"

网络架构描述

何凯明在描述网络架构时的特点：

1. 表格化呈现 - 使用表格列出层配置
2. 可视化辅助 - 配合架构图
3. 简洁符号 - 使用清晰的数学符号
4. 示例:

layer name | output size | configuration
conv1      | 112×112   | 7×7, 64, /2