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# Writing Techniques and Patterns
This file contains actionable sentence patterns, transition phrases, and writing techniques extracted from successful ML conference papers.
---
## 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..."
---
## 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)."
---
## 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.
---
## 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."
---
## 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."
---
## 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.
---
## "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**:
```markdown
Surprisingly, we observe: (i) [simple sufficient without common practice]
and (ii) [simple sufficient without common practice]
```
**Example (ViTDet Abstract)**:
```latex
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**:
```markdown
More surprisingly, under some circumstances, our [method] can compete
with the leading [competitors].
```
**Example (ViTDet Introduction)**:
```latex
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**:
```markdown
With [specific condition], our [method] can outperform the [competitors]
that use [stronger condition]. The gains are more prominent for [condition].
```
**Example**:
```latex
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
---
### "Surprisingly" Variants
#### "Interestingly" - Pattern Observation + Explanation
**Pattern**:
```markdown
Interestingly, [observation]. This is in line with the observation in [paper]
that [their finding]. [Additional explanation].
```
**Example (ViTDet)**:
```latex
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**:
```markdown
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**:
```markdown
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
---
### 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
---
## Ablation Study Writing Techniques
**Source**: Kaiming He papers (ViTDet, MeanFlows, MoCo v2)
### Table Design: Incremental Progression
**Pattern**:
```markdown
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)**:
```latex
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"
---
### Destructive Ablation: Proving Necessity
**Pattern**:
```markdown
We conduct a destructive comparison in which [wrong choice] is intentionally
performed. Meaningful results are achieved only when [correct choice].
```
**Example (MeanFlows Table 1b)**:
```latex
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)
---
### Ablation Narrative: Observation → Explanation
**Pattern 1: Observation + Literature Support**
```latex
We observe that [observation]. This is consistent with the observation in
[paper] that [their finding].
```
**Pattern 2: Observation + Hypothesis**
```latex
We hypothesize that this is because [reason 1] and also because [reason 2].
```
**Pattern 3: Observation + Theory**
```latex
[Observation]. This indicates that [theoretical explanation].
```
---
## 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
---
## 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
---
## 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
```
|