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# Writing Techniques and Patterns
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This file contains actionable sentence patterns, transition phrases, and writing techniques extracted from successful ML conference papers.
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---
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## Transition Phrases
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### Literature Review Transitions
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**Source:** Various NeurIPS/ICML papers
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**Introducing Problems:**
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- "However, these methods suffer from [limitation]."
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- "Despite recent progress, [challenge] remains unsolved."
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- "While existing approaches address [aspect], they struggle with [issue]."
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**Presenting Solutions:**
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- "To address this, we propose..."
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- "We overcome this limitation by..."
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- "Our key insight is that..."
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**Connecting to Related Work:**
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- "Building on [prior work], we extend..."
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- "Unlike approaches that [method], we instead..."
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- "Following the success of [paper], we apply..."
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### Methods Section Transitions
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**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)
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**Describing Components:**
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- "Our model consists of two main components: [A] and [B]."
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- "We divide our approach into [N] stages: [list]."
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**Explaining Rationale:**
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- "We choose this architecture because..."
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- "This formulation allows us to..."
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- "Motivated by [intuition], we design..."
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### Results Section Transitions
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**Source:** "Attention Is All You Need", NeurIPS (2017)
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**Presenting Findings:**
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- "Our method achieves [result], outperforming baselines by [margin]."
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- "As shown in Table 1, our approach..."
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- "Figure 2 demonstrates that..."
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**Analyzing Results:**
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- "These results suggest that [insight]."
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- "Notably, we observe that..."
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- "This improvement indicates that..."
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### Discussion Transitions
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**Source:** "Language Models are Few-Shot Learners", GPT-3 (2020)
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**Interpreting Findings:**
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- "These findings reveal that..."
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- "This performance gap suggests that..."
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- "The strong correlation between...indicates..."
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**Connecting to Broader Context:**
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- "Beyond the specific task, our results imply..."
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- "This has important implications for..."
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**Acknowledging Limitations:**
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- "It is important to note that our study is limited to..."
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- "While these results are promising, several questions remain..."
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---
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## Sentence Patterns
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### Claim Presentation
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**Source:** "Attention Is All You Need", NeurIPS (2017)
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**Strong Claims:**
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- "We show that [approach] achieves [result]."
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- "We demonstrate that [method] outperforms..."
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- "We prove that [technique] converges to..."
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**Nuanced Claims:**
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- "Our results suggest that [factor] contributes to..."
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- "We observe that [phenomenon] emerges when..."
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- "Experiments indicate that [approach] is particularly effective for..."
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### Technical Description
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**Source:** "Adam: A Method for Stochastic Optimization", ICLR (2015)
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**Algorithm Description:**
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- "Formally, we optimize [objective] using [method]."
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- "The update rule for [parameter] is given by..."
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- "We modify the standard [approach] by..."
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**Implementation Details:**
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- "In practice, we implement [feature] as..."
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- "For computational efficiency, we approximate..."
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- "We initialize [parameters] using..."
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### Results Presentation
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**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)
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**Quantitative Results:**
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- "Our model achieves [score] (±[std]), improving over..."
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- "On [dataset], we obtain [result], compared to..."
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- "We observe a [percentage]% improvement over baselines."
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**Statistical Reporting:**
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- "Results are averaged over N runs with different seeds."
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- "Standard deviations are shown in parentheses."
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- "The improvement is statistically significant (p<0.01)."
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---
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## Clarity Techniques
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### Active Voice Usage
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**Source:** Various well-written papers
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**Passive (avoid):**
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- "The model was trained using..."
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- "Experiments were conducted on..."
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**Active (prefer):**
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- "We trained the model using..."
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- "We conducted experiments on..."
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**Guideline:** Use active voice for actions you performed. Use passive for general facts or when the actor is unclear.
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### Specificity Over Generality
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**Source:** "Attention Is All You Need", NeurIPS (2017)
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**Vague (avoid):**
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- "This approach improves performance."
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- "The method learns good representations."
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**Specific (prefer):**
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- "This approach improves accuracy by 15%."
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- "The method learns representations that transfer to downstream tasks."
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**Guideline:** Be quantitative whenever possible. Use specific numbers and metrics.
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### Signposting
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**Source:** "BERT: Pre-training of Deep Bidirectional Transformers", NAACL (2019)
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**Section Openings:**
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- "We now describe our model architecture."
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- "We evaluate on three tasks: [list]."
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- "The results suggest three key insights:"
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**Internal Structure:**
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- "First, we [action]. Next, we [action]. Finally, we [action]."
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- "Our approach has three stages: [A], [B], and [C]."
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**Guideline:** Use explicit signposting to help tired reviewers follow your paper.
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---
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## Common Phrase Templates
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### Opening Abstract
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**Good Examples:**
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- "We introduce [method], a novel approach for [task]."
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- "We present [method], which achieves [result] by [mechanism]."
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- "We propose [framework] to address [challenge]."
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**Avoid:**
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- "In this paper, we study..." (generic)
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- "Large language models have..." (overused opening)
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### Introducing Related Work
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**Good Examples:**
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- "Recent work has shown promise in [area] [refs]."
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- "Several approaches have been proposed for [task] [refs]."
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- "The standard approach to [problem] is [method] [refs]."
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### Describing Experiments
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**Good Examples:**
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- "We evaluate on [datasets], comparing against [baselines]."
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- "We conduct ablation studies to validate [component]."
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- "To verify [claim], we experiment with [variations]."
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### Presenting Results
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**Good Examples:**
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- "Table 1 shows that our method outperforms all baselines."
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- "As shown in Figure 3, performance improves as [factor] increases."
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- "Our method achieves state-of-the-art on [task/metric]."
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### Discussing Limitations
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**Good Examples:**
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- "Our approach has limitations: [constraint]."
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- "We note that our method is currently restricted to [condition]."
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- "A key limitation is [issue], which we leave for future work."
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---
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## Writing Principles
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### From Top Papers
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**Clarity First:**
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- "Make it easy for reviewers to understand your contribution."
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- "Use concrete examples and specific language."
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- "Avoid vague or ambiguous statements."
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**Rigorous Presentation:**
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- "Provide enough detail for reproduction."
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- "Include error bars and statistical tests."
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- "Show negative results when relevant."
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**Storytelling:**
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- "Your paper tells a story: problem → approach → solution → impact."
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- "Make the narrative clear in the introduction."
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- "Each section should advance the story."
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**Honesty:**
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- "Acknowledge limitations explicitly."
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- "Don't overclaim results."
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- "Trust reviewers to appreciate honesty."
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---
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## Notes
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- **Adapt patterns**: These templates can and should be adapted to your specific context
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- **Venue matters**: Some venues prefer certain styles (check venue-specific guides)
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- **Consistency**: Use consistent terminology throughout
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- **Tone**: Maintain professional, objective tone
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- **Length**: Keep transitions concise; don't over-explain
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**Attribution:** All patterns extracted from analyzed papers with source citations for traceability.
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---
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## "Surprisingly" Findings: Multi-Level Reporting Pattern
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**Source**: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, ECCV 2022), "Mean Flows" (2025)
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**Paper Type**: Design simplification, unexpected findings
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### The Three-Level "Surprisingly" Pattern
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#### Level 1: Basic Surprise (Abstract/Opening)
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**Pattern**:
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```markdown
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Surprisingly, we observe: (i) [simple sufficient without common practice]
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and (ii) [simple sufficient without common practice]
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```
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**Example (ViTDet Abstract)**:
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```latex
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Surprisingly, we observe: (i) it is sufficient to build a simple feature
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pyramid from a single-scale feature map (without the common FPN design) and
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(ii) it is sufficient to use window attention (without shifting) aided with
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very few cross-window propagation blocks.
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```
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**Key Techniques**:
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- **Structured list**: Use (i) and (ii) to separate findings
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- **"sufficient"**: Scientific phrasing (not "optimal")
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- **"without [common practice]"**: Negative differentiation
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#### Level 2: Competitive Surprise (Introduction)
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**Pattern**:
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```markdown
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More surprisingly, under some circumstances, our [method] can compete
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with the leading [competitors].
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```
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**Example (ViTDet Introduction)**:
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```latex
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More surprisingly, under some circumstances, our plain-backbone detector,
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named ViTDet, can compete with the leading hierarchical-backbone detectors
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(e.g., Swin, MViT).
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```
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**Key Techniques**:
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- **"More surprisingly"**: Progressive emphasis
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- **"under some circumstances"**: Measured claim
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- **"can compete with"**: Not "beat", competitive
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- **Name competitors**: Specific (Swin, MViT)
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#### Level 3: Superiority Surprise (Results)
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**Pattern**:
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```markdown
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With [specific condition], our [method] can outperform the [competitors]
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that use [stronger condition]. The gains are more prominent for [condition].
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```
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**Example**:
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```latex
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With Masked Autoencoder (MAE) pre-training, our plain-backbone detector can
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outperform the hierarchical counterparts that are pre-trained on ImageNet-1K/21K
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with supervision (Figure 3). The gains are more prominent for larger model sizes.
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```
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**Key Techniques**:
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- **Specific conditions compared**: MAE vs ImageNet supervised
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- **"outperform"**: Stronger claim here (qualified by conditions)
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- **"The gains are more prominent for..."**: Pattern observation
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---
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### "Surprisingly" Variants
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#### "Interestingly" - Pattern Observation + Explanation
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**Pattern**:
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```markdown
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Interestingly, [observation]. This is in line with the observation in [paper]
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that [their finding]. [Additional explanation].
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```
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**Example (ViTDet)**:
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```latex
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Interestingly, performing propagation in the last 4 blocks is nearly as
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good as even placement. This is in line with the observation in ViT [14]
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that ViT has longer attention distance in later blocks and is more localized
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in earlier ones.
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```
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**Use when**: You have literature support for your observation
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#### "Notably" - Important Detail
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**Pattern**:
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```markdown
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Notably, [counter-intuitive result or impressive number].
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```
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**Examples**:
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- "Notably, even embedding only the interval t−r yields reasonable results."
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- "Notably, our method is self-contained and trained entirely from scratch."
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**Use when**: Emphasizing importance or counter-intuitive finding
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#### "It is worth noting that" - Caveat/Clarification
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**Pattern**:
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```markdown
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It is worth noting that [technical caveat or clarification].
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```
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**Examples**:
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- "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."
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- "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."
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**Use when**: Preventing misunderstanding or clarifying technical details
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---
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### When to Use "Surprisingly"
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**DO use**:
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- When finding genuinely contradicts common practice
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- When simple solution works as well as complex one
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- When you have explanation (literature, hypothesis, theory)
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- With measured claims ("under some circumstances", "can compete")
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- With "sufficient" not "optimal"
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**DON'T use**:
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- For incremental improvements (use "additionally" instead)
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- Without explanation/justification
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- Overgeneralizing ("always", "proves")
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- For expected results
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---
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## Ablation Study Writing Techniques
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**Source**: Kaiming He papers (ViTDet, MeanFlows, MoCo v2)
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### Table Design: Incremental Progression
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**Pattern**:
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```markdown
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Table X: [Component] Ablation
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┌──────────────────────────────────────────┐
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│ no [component] | AP | Δ │
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│ (a) [common variant] | AP | +X.X │
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│ (b) [another variant] | AP | +Y.Y │
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│ (c) ours: simple | AP | +Z.Z ✓ │
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└──────────────────────────────────────────┘
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```
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**Example (ViTDet Table 1)**:
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```latex
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pyramid design APbox APmask
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─────────────────────────────────────────
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no feature pyramid 47.8 42.5
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(a) FPN, 4-stage 50.3 44.9
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(b) FPN, last-map 50.9 45.3
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(c) simple feature pyramid 51.2 45.5
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```
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**Techniques**:
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- **Baseline**: "no [X]" shows it's needed
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- **(a), (b), (c)**: Progressive variations
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- **Δ标注**: (+2.5) - Show incremental gains
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- **Correspondence**: "The entries (a-c) correspond to Figure X (a-c)"
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- **Conclusion**: "our simple pyramid is sufficient"
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---
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### Destructive Ablation: Proving Necessity
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**Pattern**:
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```markdown
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We conduct a destructive comparison in which [wrong choice] is intentionally
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performed. Meaningful results are achieved only when [correct choice].
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```
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**Example (MeanFlows Table 1b)**:
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```latex
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In Tab. 1b, we conduct a destructive comparison in which incorrect JVP
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computation is intentionally performed.
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jvp tangent FID, 1-NFE
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(v, 0, 1) [correct] 61.06
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(v, 0, 0) [wrong] 268.06
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(v, 1, 0) [wrong] 329.22
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(v, 1, 1) [wrong] 137.96
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It shows that meaningful results are achieved only when the JVP computation
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is correct.
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```
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**Use when**: You need to prove a design choice is necessary (not just optional)
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---
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### Ablation Narrative: Observation → Explanation
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**Pattern 1: Observation + Literature Support**
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```latex
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We observe that [observation]. This is consistent with the observation in
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[paper] that [their finding].
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```
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**Pattern 2: Observation + Hypothesis**
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```latex
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We hypothesize that this is because [reason 1] and also because [reason 2].
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```
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**Pattern 3: Observation + Theory**
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```latex
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[Observation]. This indicates that [theoretical explanation].
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```
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---
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## Theory-Driven Paper Keywords
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**Source**: Kaiming He et al., "Mean Flows for One-step Generative Modeling" (2025)
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### Naturalness Keywords (use to describe your theory)
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- **"naturally"** - "This naturally leads to..."
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- **"intrinsic"** - "intrinsic relation between..."
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- **"well-defined"** - "well-defined problem"
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- **"principled"** - "principled basis for..."
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- **"first principles"** - "from first principles"
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- **"solely originated from"** - "solely from definition"
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### Independence Keywords
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- **"does not depend on"** - Theory independence from implementation
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- **"independent of"** - Independent of specific choices
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- **"self-contained"** - System independence
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- **"from scratch"** - No external dependencies
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- **"without any X"** - Negative list (what you don't need)
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### Differentiation Keywords
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- **"in contrast to"** - Conceptual contrast
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- **"unlike"** - Direct comparison
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- **"typically"** - "typically modeled" (their approach)
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- **"prior works typically rely on"** - Their limitation
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- **"imposed as"** - Artificial constraint (theirs)
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### Avoid (Too Promotional)
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- ❌ "revolutionary" - Let others say it
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- ❌ "breakthrough" - Overused
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- ❌ "completely eliminates" - Too absolute
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- ✅ "significantly outperforms" - Strong but measured
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- ✅ "substantial improvement" - Professional
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---
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## Design Simplification Paper Keywords
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**Source**: Kaiming He et al., "Exploring Plain Vision Transformer Backbones for Object Detection" (ViTDet, 2022)
|
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|
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### Philosophy Keywords
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- **"minimal"** - "minimal adaptations"
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- **"sufficient"** - "is sufficient to" (not "optimal")
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- **"simple"** - "simple feature pyramid"
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- **"plain"** - "plain backbone"
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- **"decouple"** - "decouple pre-training from fine-tuning"
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- **"independence"** - "independence of upstream vs downstream"
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### Direction Keywords
|
||||
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- **"pursue a different direction"** - Clear positioning
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||||
- **"in contrast to"** - Differentiation
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- **"abandons"** - What you give up (respectfully)
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- **"enables"** - What your approach allows
|
||||
|
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### Measured Claim Keywords
|
||||
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- **"under some circumstances"** - Not always
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- **"can compete with"** - Competitive, not dominant
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- **"more prominent for"** - When effect is stronger
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||||
- **"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
|
||||
```
|
||||
Reference in New Issue
Block a user