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+---
+name: ml-paper-writing
+description: Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.
+version: 1.0.0
+author: Orchestra Research
+license: MIT
+tags: [Academic Writing, NeurIPS, ICML, ICLR, ACL, AAAI, COLM, LaTeX, Paper Writing, Citations, Research]
+dependencies: [semanticscholar, arxiv, habanero, requests]
+---
+
+# ML Paper Writing for Top AI Conferences
+
+Expert-level guidance for writing publication-ready papers targeting **NeurIPS, ICML, ICLR, ACL, AAAI, and COLM**. This skill combines writing philosophy from top researchers (Nanda, Farquhar, Karpathy, Lipton, Steinhardt) with practical tools: LaTeX templates, citation verification APIs, and conference checklists.
+
+## Default operating order
+
+Use this skill in the following order unless the task is unusually narrow:
+1. lock the operating mode from `references/OPERATING-MODES.md`,
+2. understand the repo or draft context,
+3. use `references/citation-workflow.md` as the **canonical citation authority**,
+4. load venue- or template-specific references only after the main writing path is clear.
+
+Google Scholar may still help with manual discovery, but it is **not** the canonical verification authority in this skill. Default verification should use programmatic sources such as Semantic Scholar, CrossRef, and arXiv.
+
+## Core Philosophy: Collaborative Writing
+
+**Paper writing is collaborative, but Claude should be proactive in delivering drafts.**
+
+The typical workflow starts with a research repository containing code, results, and experimental artifacts. Claude's role is to:
+
+1. **Understand the project** by exploring the repo, results, and existing documentation
+2. **Deliver a complete first draft** when confident about the contribution
+3. **Search literature** using web search and APIs to find relevant citations
+4. **Refine through feedback cycles** when the scientist provides input
+5. **Ask for clarification** only when genuinely uncertain about key decisions
+
+**Key Principle**: Be proactive. If the repo and results are clear, deliver a full draft. Don't block waiting for feedback on every section—scientists are busy. Produce something concrete they can react to, then iterate based on their response.
+
+---
+
+## ⚠️ CRITICAL: Never Hallucinate Citations
+
+**This is the most important rule in academic writing with AI assistance.**
+
+### The Problem
+AI-generated citations have a **~40% error rate**. Hallucinated references—papers that don't exist, wrong authors, incorrect years, fabricated DOIs—are a serious form of academic misconduct that can result in desk rejection or retraction.
+
+### The Rule
+**NEVER generate BibTeX entries from memory. ALWAYS fetch programmatically.**
+
+| Action | ✅ Correct | ❌ Wrong |
+|--------|-----------|----------|
+| Adding a citation | Search API → verify → fetch BibTeX | Write BibTeX from memory |
+| Uncertain about a paper | Mark as `[CITATION NEEDED]` | Guess the reference |
+| Can't find exact paper | Note: "placeholder - verify" | Invent similar-sounding paper |
+
+### When You Can't Verify a Citation
+
+If you cannot programmatically verify a citation, you MUST:
+
+```latex
+% EXPLICIT PLACEHOLDER - requires human verification
+\cite{PLACEHOLDER_author2024_verify_this}  % TODO: Verify this citation exists
+```
+
+**Always tell the scientist**: "I've marked [X] citations as placeholders that need verification. I could not confirm these papers exist."
+
+### Recommended: Install Exa MCP for Paper Search
+
+For the best paper search experience, install **Exa MCP** which provides real-time academic search:
+
+**Claude Code:**
+```bash
+claude mcp add exa -- npx -y mcp-remote "https://mcp.exa.ai/mcp"
+```
+
+**Cursor / VS Code** (add to MCP settings):
+```json
+{
+  "mcpServers": {
+    "exa": {
+      "type": "http",
+      "url": "https://mcp.exa.ai/mcp"
+    }
+  }
+}
+```
+
+Exa MCP enables searches like:
+- "Find papers on RLHF for language models published after 2023"
+- "Search for transformer architecture papers by Vaswani"
+- "Get recent work on sparse autoencoders for interpretability"
+
+Then verify results with Semantic Scholar API and fetch BibTeX via DOI.
+
+---
+
+## Workflow 0: Starting from a Research Repository
+
+When beginning paper writing, start by understanding the project:
+
+```
+Project Understanding:
+- [ ] Step 1: Explore the repository structure
+- [ ] Step 2: Read README, existing docs, and key results
+- [ ] Step 3: Identify the main contribution with the scientist
+- [ ] Step 4: Find papers already cited in the codebase
+- [ ] Step 5: Search for additional relevant literature
+- [ ] Step 6: Outline the paper structure together
+- [ ] Step 7: Draft sections iteratively with feedback
+```
+
+**Step 1: Explore the Repository**
+
+```bash
+# Understand project structure
+ls -la
+find . -name "*.py" | head -20
+find . -name "*.md" -o -name "*.txt" | xargs grep -l -i "result\|conclusion\|finding"
+```
+
+Look for:
+- `README.md` - Project overview and claims
+- `results/`, `outputs/`, `experiments/` - Key findings
+- `configs/` - Experimental settings
+- Existing `.bib` files or citation references
+- Any draft documents or notes
+
+**Step 2: Identify Existing Citations**
+
+Check for papers already referenced in the codebase:
+
+```bash
+# Find existing citations
+grep -r "arxiv\|doi\|cite" --include="*.md" --include="*.bib" --include="*.py"
+find . -name "*.bib"
+```
+
+These are high-signal starting points for Related Work—the scientist has already deemed them relevant.
+
+**Step 3: Clarify the Contribution**
+
+Before writing, explicitly confirm with the scientist:
+
+> "Based on my understanding of the repo, the main contribution appears to be [X].
+> The key results show [Y]. Is this the framing you want for the paper,
+> or should we emphasize different aspects?"
+
+**Never assume the narrative—always verify with the human.**
+
+**Step 4: Search for Additional Literature**
+
+Use web search to find relevant papers:
+
+```
+Search queries to try:
+- "[main technique] + [application domain]"
+- "[baseline method] comparison"
+- "[problem name] state-of-the-art"
+- Author names from existing citations
+```
+
+Then verify and retrieve BibTeX using the citation workflow below.
+
+**Step 5: Deliver a First Draft**
+
+**Be proactive—deliver a complete draft rather than asking permission for each section.**
+
+If the repo provides clear results and the contribution is apparent:
+1. Write the full first draft end-to-end
+2. Present the complete draft for feedback
+3. Iterate based on scientist's response
+
+If genuinely uncertain about framing or major claims:
+1. Draft what you can confidently
+2. Flag specific uncertainties: "I framed X as the main contribution—let me know if you'd prefer to emphasize Y instead"
+3. Continue with the draft rather than blocking
+
+**Questions to include with the draft** (not before):
+- "I emphasized X as the main contribution—adjust if needed"
+- "I highlighted results A, B, C—let me know if others are more important"
+- "Related work section includes [papers]—add any I missed"
+
+---
+
+## When to Use This Skill
+
+Use this skill when:
+- **Starting from a research repo** to write a paper
+- **Drafting or revising** specific sections
+- **Conducting literature reviews** and finding related work
+- **Discovering recent papers** in your research area
+- **Finding and verifying citations** for related work
+- **Formatting** for conference submission
+- **Resubmitting** to a different venue (format conversion)
+- **Iterating** on drafts with scientist feedback
+
+**Always remember**: First drafts are starting points for discussion, not final outputs.
+
+---
+
+## Workflow: Literature Research & Paper Discovery
+
+When conducting literature reviews, finding related work, or discovering recent papers, use this workflow to systematically search, evaluate, and select ML papers.
+
+### Workflow 5: Finding and Evaluating Papers
+
+```
+Literature Research Process:
+- [ ] Step 1: Define search scope and keywords
+- [ ] Step 2: Search arXiv and academic databases
+- [ ] Step 3: Screen papers by title/abstract
+- [ ] Step 4: Evaluate paper quality (5 dimensions)
+- [ ] Step 5: Select top papers and extract citations
+- [ ] Step 6: Verify citations programmatically
+```
+
+**Step 1: Define Search Scope**
+
+Identify specific research areas, methods, or applications:
+- **Technique-focused**: `transformer architecture`, `graph neural networks`, `self-supervised learning`
+- **Application-focused**: `medical image analysis`, `reinforcement learning for robotics`, `language model alignment`
+- **Problem-focused**: `out-of-distribution generalization`, `continual learning`, `fairness in ML`
+
+**Step 2: Search arXiv**
+
+Use arXiv search with targeted keywords:
+```
+URL Pattern:
+https://arxiv.org/search/?searchtype=all&query=KEYWORDS&abstracts=show&order=-announced_date_first
+
+Example Searches:
+- https://arxiv.org/search/?searchtype=all&query=graph+neural+networks&abstracts=show&order=-announced_date_first
+- https://arxiv.org/search/?cat:cs.LG+AND+all:transformer&abstracts=show&order=-announced_date_first
+```
+
+**Tips:**
+- Combine keywords with `+` for AND
+- Filter by categories: `cs.LG`, `cs.AI`, `cs.CV`, `cs.CL`
+- Sort by `announced_date_first` for recent papers
+- Use Chrome MCP tools when available for automation
+
+**Step 3: Screen Papers**
+
+Quick screening by title and abstract:
+- Relevance to research topic
+- Novelty of contribution
+- Venue/reputation of authors
+- Code availability (check for GitHub links)
+
+**Step 4: Evaluate Quality**
+
+Use the 5-dimension quality criteria:
+
+| Dimension | Weight | Evaluation Focus |
+|-----------|--------|------------------|
+| **Innovation** | 30% | Novelty and originality |
+| **Method Completeness** | 25% | Clarity and reproducibility |
+| **Experimental Thoroughness** | 25% | Validation depth |
+| **Writing Quality** | 10% | Presentation clarity |
+| **Relevance & Impact** | 10% | Domain importance |
+
+**Scoring**: Rate each dimension 1-5, calculate weighted total
+
+**Step 5: Select and Extract**
+
+- Rank papers by total score
+- Select top papers for detailed review
+- Extract metadata: title, authors, arXiv ID, abstract
+- Note code repository links
+
+**Step 6: Verify Citations**
+
+For selected papers, verify citations using Semantic Scholar API:
+- Fetch BibTeX programmatically via DOI
+- Mark unverified citations as `[CITATION NEEDED]`
+- Store in bibliography with verification status
+
+### When to Use Literature Research
+
+Use this workflow when:
+- **Starting a new project**: Find related work and baselines
+- **Writing Related Work section**: Discover recent papers in your area
+- **Staying updated**: Track recent publications in your field
+- **Finding baselines**: Identify state-of-the-art methods for comparison
+- **Literature review**: Comprehensive survey of research area
+
+### Quality Thresholds
+
+- **Excellent**: 4.0+ (include definitely)
+- **Good**: 3.5-3.9 (include if relevant)
+- **Fair**: 3.0-3.4 (include if highly relevant)
+- **Poor**: <3.0 (exclude unless essential)
+
+### Reference Files
+
+For detailed literature research guidance:
+- **`references/literature-research/arxiv-search-guide.md`** - arXiv search strategies and URL patterns
+- **`references/literature-research/paper-quality-criteria.md`** - Detailed 5-dimension evaluation rubrics
+
+---
+
+## Knowledge Base: Paper-Miner Global Writing Memory
+
+This skill consumes a **single canonical writing memory** maintained by `paper-miner`:
+
+- `references/knowledge/paper-miner-writing-memory.md`
+
+This memory is **global**, not project-specific.
+
+Even when `paper-miner` is invoked while working inside a specific repository, it still writes mined writing knowledge only into this one global memory. It does **not** maintain project-local writing memory.
+
+### Canonical memory structure
+
+The maintained memory contains these sections:
+
+| Section | Purpose |
+|----------|---------|
+| `Writing patterns mined` | Reusable rhetorical and claim-evidence patterns |
+| `Structure signals` | Section flow, paragraph progression, and paper organization signals |
+| `Reusable phrasing` | Transition phrases, framing templates, and concise wording |
+| `Venue-specific signals` | Visible venue-facing style and convention cues |
+| `How this helps our writing` | Practical guidance for future drafts, reports, and rebuttals |
+| `Source index` | Source attribution for mined papers |
+
+### How the memory is maintained
+
+The **paper-miner agent** reads papers and merges reusable writing knowledge into this one file:
+
+```text
+You: "Learn writing patterns from this paper: path/to/paper.pdf"
+↓
+paper-miner analyzes the paper
+↓
+Extracts reusable writing signals
+↓
+Updates paper-miner-writing-memory.md
+↓
+ml-paper-writing reuses that memory later
+```
+
+### When to use this memory
+
+Use the global paper-miner memory when you need:
+- structure inspiration for intros, methods, results, or discussion,
+- reusable transition phrases or framing templates,
+- venue-facing writing signals,
+- rebuttal phrasing and response structure ideas,
+- examples of how strong papers support and sequence claims.
+
+### Default read order
+
+When drafting or revising with `ml-paper-writing`, read this memory **before** writing if the task involves:
+- introduction framing,
+- related work organization,
+- method exposition style,
+- results narration,
+- discussion framing,
+- venue-facing polishing.
+
+Use this read order:
+1. `references/knowledge/paper-miner-writing-memory.md`
+2. repo-local evidence and experiment artifacts
+3. cited papers or notes if needed
+4. venue template and formatting constraints
+
+Read narrowly, not exhaustively:
+- first scan `How this helps our writing`,
+- then check `Writing patterns mined` and `Structure signals`,
+- then inspect `Reusable phrasing` only for concrete wording help,
+- use `Venue-specific signals` when targeting a known venue.
+
+### Contribution rule
+
+Every paper mined by `paper-miner` should improve the same global memory.
+
+Do not scatter newly mined knowledge across multiple maintained files.
+Do not create project-specific paper-miner memory.
+Do not duplicate near-identical patterns from the same source.
+
+See `references/knowledge/README.md` for the detailed knowledge-base contract.
+
+## Balancing Proactivity and Collaboration
+
+**Default: Be proactive. Deliver drafts, then iterate.**
+
+| Confidence Level | Action |
+|-----------------|--------|
+| **High** (clear repo, obvious contribution) | Write full draft, deliver, iterate on feedback |
+| **Medium** (some ambiguity) | Write draft with flagged uncertainties, continue |
+| **Low** (major unknowns) | Ask 1-2 targeted questions, then draft |
+
+**Draft first, ask with the draft** (not before):
+
+| Section | Draft Autonomously | Flag With Draft |
+|---------|-------------------|-----------------|
+| Abstract | Yes | "Framed contribution as X—adjust if needed" |
+| Introduction | Yes | "Emphasized problem Y—correct if wrong" |
+| Methods | Yes | "Included details A, B, C—add missing pieces" |
+| Experiments | Yes | "Highlighted results 1, 2, 3—reorder if needed" |
+| Related Work | Yes | "Cited papers X, Y, Z—add any I missed" |
+
+**Only block for input when:**
+- Target venue is unclear (affects page limits, framing)
+- Multiple contradictory framings seem equally valid
+- Results seem incomplete or inconsistent
+- Explicit request to review before continuing
+
+**Don't block for:**
+- Word choice decisions
+- Section ordering
+- Which specific results to show (make a choice, flag it)
+- Citation completeness (draft with what you find, note gaps)
+
+---
+
+## The Narrative Principle
+
+**The single most critical insight**: Your paper is not a collection of experiments—it's a story with one clear contribution supported by evidence.
+
+Every successful ML paper centers on what Neel Nanda calls "the narrative": a short, rigorous, evidence-based technical story with a takeaway readers care about.
+
+**Three Pillars (must be crystal clear by end of introduction):**
+
+| Pillar | Description | Example |
+|--------|-------------|---------|
+| **The What** | 1-3 specific novel claims within cohesive theme | "We prove that X achieves Y under condition Z" |
+| **The Why** | Rigorous empirical evidence supporting claims | Strong baselines, experiments distinguishing hypotheses |
+| **The So What** | Why readers should care | Connection to recognized community problems |
+
+**If you cannot state your contribution in one sentence, you don't yet have a paper.**
+
+---
+
+## Paper Structure Workflow
+
+### Workflow 1: Writing a Complete Paper (Iterative)
+
+Copy this checklist and track progress. **Each step involves drafting → feedback → revision:**
+
+```
+Paper Writing Progress:
+- [ ] Step 1: Define the one-sentence contribution (with scientist)
+- [ ] Step 2: Draft Figure 1 → get feedback → revise
+- [ ] Step 3: Draft abstract → get feedback → revise
+- [ ] Step 4: Draft introduction → get feedback → revise
+- [ ] Step 5: Draft methods → get feedback → revise
+- [ ] Step 6: Draft experiments → get feedback → revise
+- [ ] Step 7: Draft related work → get feedback → revise
+- [ ] Step 8: Draft limitations → get feedback → revise
+- [ ] Step 9: Complete paper checklist (required)
+- [ ] Step 10: Final review cycle and submission
+```
+
+**Step 1: Define the One-Sentence Contribution**
+
+**This step requires explicit confirmation from the scientist.**
+
+Before writing anything, articulate and verify:
+- What is the single thing your paper contributes?
+- What was not obvious or present before your work?
+
+> "I propose framing the contribution as: '[one sentence]'. Does this capture
+> what you see as the main takeaway? Should we adjust the emphasis?"
+
+**Step 2: Draft Figure 1**
+
+Figure 1 deserves special attention—many readers skip directly to it.
+- Convey core idea, approach, or most compelling result
+- Use vector graphics (PDF/EPS for plots)
+- Write captions that stand alone without main text
+- Ensure readability in black-and-white (8% of men have color vision deficiency)
+
+**Step 3: Write Abstract (5-Sentence Formula)**
+
+From Sebastian Farquhar (DeepMind):
+
+```
+1. What you achieved: "We introduce...", "We prove...", "We demonstrate..."
+2. Why this is hard and important
+3. How you do it (with specialist keywords for discoverability)
+4. What evidence you have
+5. Your most remarkable number/result
+```
+
+**Delete** generic openings like "Large language models have achieved remarkable success..."
+
+**Step 4: Write Introduction (1-1.5 pages max)**
+
+Must include:
+- 2-4 bullet contribution list (max 1-2 lines each in two-column format)
+- Clear problem statement
+- Brief approach overview
+- Methods should start by page 2-3 maximum
+
+**Step 5: Methods Section**
+
+Enable reimplementation:
+- Conceptual outline or pseudocode
+- All hyperparameters listed
+- Architectural details sufficient for reproduction
+- Present final design decisions; ablations go in experiments
+
+**Step 6: Experiments Section**
+
+For each experiment, explicitly state:
+- What claim it supports
+- How it connects to main contribution
+- Experimental setting (details in appendix)
+- What to observe: "the blue line shows X, which demonstrates Y"
+
+Requirements:
+- Error bars with methodology (standard deviation vs standard error)
+- Hyperparameter search ranges
+- Compute infrastructure (GPU type, total hours)
+- Seed-setting methods
+
+**Step 7: Related Work**
+
+Organize methodologically, not paper-by-paper:
+
+**Good:** "One line of work uses Floogledoodle's assumption [refs] whereas we use Doobersnoddle's assumption because..."
+
+**Bad:** "Snap et al. introduced X while Crackle et al. introduced Y."
+
+Cite generously—reviewers likely authored relevant papers.
+
+**Step 8: Limitations Section (REQUIRED)**
+
+All major conferences require this. Counter-intuitively, honesty helps:
+- Reviewers are instructed not to penalize honest limitation acknowledgment
+- Pre-empt criticisms by identifying weaknesses first
+- Explain why limitations don't undermine core claims
+
+**Step 9: Paper Checklist**
+
+NeurIPS, ICML, and ICLR all require paper checklists. See [references/checklists.md](references/checklists.md).
+
+---
+
+## Writing Philosophy for Top ML Conferences
+
+**This section distills the most important writing principles from leading ML researchers.** These aren't optional style suggestions—they're what separates accepted papers from rejected ones.
+
+> "A paper is a short, rigorous, evidence-based technical story with a takeaway readers care about." — Neel Nanda
+
+### The Sources Behind This Guidance
+
+This skill synthesizes writing philosophy from researchers who have published extensively at top venues:
+
+| Source | Key Contribution | Link |
+|--------|-----------------|------|
+| **Neel Nanda** (Google DeepMind) | The Narrative Principle, What/Why/So What framework | [How to Write ML Papers](https://www.alignmentforum.org/posts/eJGptPbbFPZGLpjsp/highly-opinionated-advice-on-how-to-write-ml-papers) |
+| **Sebastian Farquhar** (DeepMind) | 5-sentence abstract formula | [How to Write ML Papers](https://sebastianfarquhar.com/on-research/2024/11/04/how_to_write_ml_papers/) |
+| **Gopen & Swan** | 7 principles of reader expectations | [Science of Scientific Writing](https://cseweb.ucsd.edu/~swanson/papers/science-of-writing.pdf) |
+| **Zachary Lipton** | Word choice, eliminating hedging | [Heuristics for Scientific Writing](https://www.approximatelycorrect.com/2018/01/29/heuristics-technical-scientific-writing-machine-learning-perspective/) |
+| **Jacob Steinhardt** (UC Berkeley) | Precision, consistent terminology | [Writing Tips](https://bounded-regret.ghost.io/) |
+| **Ethan Perez** (Anthropic) | Micro-level clarity tips | [Easy Paper Writing Tips](https://ethanperez.net/easy-paper-writing-tips/) |
+| **Andrej Karpathy** | Single contribution focus | Various lectures |
+
+**For deeper dives into any of these, see:**
+- [references/writing-guide.md](references/writing-guide.md) - Full explanations with examples
+- [references/sources.md](references/sources.md) - Complete bibliography
+
+### Time Allocation (From Neel Nanda)
+
+Spend approximately **equal time** on each of:
+1. The abstract
+2. The introduction
+3. The figures
+4. Everything else combined
+
+**Why?** Most reviewers form judgments before reaching your methods. Readers encounter your paper as: **title → abstract → introduction → figures → maybe the rest.**
+
+### Writing Style Guidelines
+
+#### Sentence-Level Clarity (Gopen & Swan's 7 Principles)
+
+These principles are based on how readers actually process prose. Violating them forces readers to spend cognitive effort on structure rather than content.
+
+| Principle | Rule | Example |
+|-----------|------|---------|
+| **Subject-verb proximity** | Keep subject and verb close | ❌ "The model, which was trained on..., achieves" → ✅ "The model achieves... after training on..." |
+| **Stress position** | Place emphasis at sentence ends | ❌ "Accuracy improves by 15% when using attention" → ✅ "When using attention, accuracy improves by **15%**" |
+| **Topic position** | Put context first, new info after | ✅ "Given these constraints, we propose..." |
+| **Old before new** | Familiar info → unfamiliar info | Link backward, then introduce new |
+| **One unit, one function** | Each paragraph makes one point | Split multi-point paragraphs |
+| **Action in verb** | Use verbs, not nominalizations | ❌ "We performed an analysis" → ✅ "We analyzed" |
+| **Context before new** | Set stage before presenting | Explain before showing equation |
+
+**Full 7 principles with detailed examples:** See [references/writing-guide.md](references/writing-guide.md#the-7-principles-of-reader-expectations)
+
+#### Micro-Level Tips (Ethan Perez)
+
+These small changes accumulate into significantly clearer prose:
+
+- **Minimize pronouns**: ❌ "This shows..." → ✅ "This result shows..."
+- **Verbs early**: Position verbs near sentence start
+- **Unfold apostrophes**: ❌ "X's Y" → ✅ "The Y of X" (when awkward)
+- **Delete filler words**: "actually," "a bit," "very," "really," "basically," "quite," "essentially"
+
+**Full micro-tips with examples:** See [references/writing-guide.md](references/writing-guide.md#micro-level-writing-tips)
+
+#### Word Choice (Zachary Lipton)
+
+- **Be specific**: ❌ "performance" → ✅ "accuracy" or "latency" (say what you mean)
+- **Eliminate hedging**: Drop "may" and "can" unless genuinely uncertain
+- **Avoid incremental vocabulary**: ❌ "combine," "modify," "expand" → ✅ "develop," "propose," "introduce"
+- **Delete intensifiers**: ❌ "provides *very* tight approximation" → ✅ "provides tight approximation"
+
+#### Precision Over Brevity (Jacob Steinhardt)
+
+- **Consistent terminology**: Different terms for same concept creates confusion. Pick one and stick with it.
+- **State assumptions formally**: Before theorems, list all assumptions explicitly
+- **Intuition + rigor**: Provide intuitive explanations alongside formal proofs
+
+### What Reviewers Actually Read
+
+Understanding reviewer behavior helps prioritize your effort:
+
+| Paper Section | % Reviewers Who Read | Implication |
+|---------------|---------------------|-------------|
+| Abstract | 100% | Must be perfect |
+| Introduction | 90%+ (skimmed) | Front-load contribution |
+| Figures | Examined before methods | Figure 1 is critical |
+| Methods | Only if interested | Don't bury the lede |
+| Appendix | Rarely | Put only supplementary details |
+
+**Bottom line**: If your abstract and intro don't hook reviewers, they may never read your brilliant methods section.
+
+---
+
+## Conference Requirements Quick Reference
+
+| Conference | Page Limit | Extra for Camera-Ready | Key Requirement |
+|------------|------------|------------------------|-----------------|
+| **NeurIPS 2025** | 9 pages | +0 | Mandatory checklist, lay summary for accepted |
+| **ICML 2026** | 8 pages | +1 | Broader Impact Statement required |
+| **ICLR 2026** | 9 pages | +1 | LLM disclosure required, reciprocal reviewing |
+| **ACL 2025** | 8 pages (long) | varies | Limitations section mandatory |
+| **AAAI 2026** | 7 pages | +1 | Strict style file adherence |
+| **COLM 2025** | 9 pages | +1 | Focus on language models |
+
+**Universal Requirements:**
+- Double-blind review (anonymize submissions)
+- References don't count toward page limit
+- Appendices unlimited but reviewers not required to read
+- LaTeX required for all venues
+
+**LaTeX Templates:** See [templates/](templates/) directory for all conference templates.
+
+---
+
+## Using LaTeX Templates Properly
+
+### Workflow 4: Starting a New Paper from Template
+
+**Always copy the entire template directory first, then write within it.**
+
+```
+Template Setup Checklist:
+- [ ] Step 1: Copy entire template directory to new project
+- [ ] Step 2: Verify template compiles as-is (before any changes)
+- [ ] Step 3: Read the template's example content to understand structure
+- [ ] Step 4: Replace example content section by section
+- [ ] Step 5: Keep template comments/examples as reference until done
+- [ ] Step 6: Clean up template artifacts only at the end
+```
+
+**Step 1: Copy the Full Template**
+
+```bash
+# Create your paper directory with the complete template
+cp -r templates/neurips2025/ ~/papers/my-new-paper/
+cd ~/papers/my-new-paper/
+
+# Verify structure is complete
+ls -la
+# Should see: main.tex, neurips.sty, Makefile, etc.
+```
+
+**⚠️ IMPORTANT**: Copy the ENTIRE directory, not just `main.tex`. Templates include:
+- Style files (`.sty`) - required for compilation
+- Bibliography styles (`.bst`) - required for references
+- Example content - useful as reference
+- Makefiles - for easy compilation
+
+**Step 2: Verify Template Compiles First**
+
+Before making ANY changes, compile the template as-is:
+
+```bash
+# Using latexmk (recommended)
+latexmk -pdf main.tex
+
+# Or manual compilation
+pdflatex main.tex
+bibtex main
+pdflatex main.tex
+pdflatex main.tex
+```
+
+If the unmodified template doesn't compile, fix that first. Common issues:
+- Missing TeX packages → install via `tlmgr install <package>`
+- Wrong TeX distribution → use TeX Live (recommended)
+
+**Step 3: Keep Template Content as Reference**
+
+Don't immediately delete all example content. Instead:
+
+```latex
+% KEEP template examples commented out as you write
+% This shows you the expected format
+
+% Template example (keep for reference):
+% \begin{figure}[t]
+%   \centering
+%   \includegraphics[width=0.8\linewidth]{example-image}
+%   \caption{Template shows caption style}
+% \end{figure}
+
+% Your actual figure:
+\begin{figure}[t]
+  \centering
+  \includegraphics[width=0.8\linewidth]{your-figure.pdf}
+  \caption{Your caption following the same style.}
+\end{figure}
+```
+
+**Step 4: Replace Content Section by Section**
+
+Work through the paper systematically:
+
+```
+Replacement Order:
+1. Title and authors (anonymize for submission)
+2. Abstract
+3. Introduction
+4. Methods
+5. Experiments
+6. Related Work
+7. Conclusion
+8. References (your .bib file)
+9. Appendix
+```
+
+For each section:
+1. Read the template's example content
+2. Note any special formatting or macros used
+3. Replace with your content following the same patterns
+4. Compile frequently to catch errors early
+
+**Step 5: Use Template Macros**
+
+Templates often define useful macros. Check the preamble for:
+
+```latex
+% Common template macros to use:
+\newcommand{\method}{YourMethodName}  % Consistent method naming
+\newcommand{\eg}{e.g.,\xspace}        % Proper abbreviations
+\newcommand{\ie}{i.e.,\xspace}
+\newcommand{\etal}{\textit{et al.}\xspace}
+```
+
+**Step 6: Clean Up Only at the End**
+
+Only remove template artifacts when paper is nearly complete:
+
+```latex
+% BEFORE SUBMISSION - remove these:
+% - Commented-out template examples
+% - Unused packages
+% - Template's example figures/tables
+% - Lorem ipsum or placeholder text
+
+% KEEP these:
+% - All style files (.sty)
+% - Bibliography style (.bst)
+% - Required packages from template
+% - Any custom macros you're using
+```
+
+### Template Pitfalls to Avoid
+
+| Pitfall | Problem | Solution |
+|---------|---------|----------|
+| Copying only `main.tex` | Missing `.sty`, won't compile | Copy entire directory |
+| Modifying `.sty` files | Breaks conference formatting | Never edit style files |
+| Adding random packages | Conflicts, breaks template | Only add if necessary |
+| Deleting template content too early | Lose formatting reference | Keep as comments until done |
+| Not compiling frequently | Errors accumulate | Compile after each section |
+
+### Quick Template Reference
+
+| Conference | Main File | Key Style File | Notes |
+|------------|-----------|----------------|-------|
+| NeurIPS 2025 | `main.tex` | `neurips.sty` | Has Makefile |
+| ICML 2026 | `example_paper.tex` | `icml2026.sty` | Includes algorithm packages |
+| ICLR 2026 | `iclr2026_conference.tex` | `iclr2026_conference.sty` | Has math_commands.tex |
+| ACL | `acl_latex.tex` | `acl.sty` | Strict formatting |
+| AAAI 2026 | `aaai2026-unified-template.tex` | `aaai2026.sty` | Very strict compliance |
+| COLM 2025 | `colm2025_conference.tex` | `colm2025_conference.sty` | Similar to ICLR |
+
+---
+
+## Conference Resubmission & Format Conversion
+
+When a paper is rejected or withdrawn from one venue and resubmitted to another, format conversion is required. This is a common workflow in ML research.
+
+### Workflow 3: Converting Between Conference Formats
+
+```
+Format Conversion Checklist:
+- [ ] Step 1: Identify source and target template differences
+- [ ] Step 2: Create new project with target template
+- [ ] Step 3: Copy content sections (not preamble)
+- [ ] Step 4: Adjust page limits and content
+- [ ] Step 5: Update conference-specific requirements
+- [ ] Step 6: Verify compilation and formatting
+```
+
+**Step 1: Key Template Differences**
+
+| From → To | Page Change | Key Adjustments |
+|-----------|-------------|-----------------|
+| NeurIPS → ICML | 9 → 8 pages | Cut 1 page, add Broader Impact if missing |
+| ICML → ICLR | 8 → 9 pages | Can expand experiments, add LLM disclosure |
+| NeurIPS → ACL | 9 → 8 pages | Restructure for NLP conventions, add Limitations |
+| ICLR → AAAI | 9 → 7 pages | Significant cuts needed, strict style adherence |
+| Any → COLM | varies → 9 | Reframe for language model focus |
+
+**Step 2: Content Migration (NOT Template Merge)**
+
+**Never copy LaTeX preambles between templates.** Instead:
+
+```bash
+# 1. Start fresh with target template
+cp -r templates/icml2026/ new_submission/
+
+# 2. Copy ONLY content sections from old paper
+# - Abstract text
+# - Section content (between \section{} commands)
+# - Figures and tables
+# - Bibliography entries
+
+# 3. Paste into target template structure
+```
+
+**Step 3: Adjusting for Page Limits**
+
+When cutting pages (e.g., NeurIPS 9 → AAAI 7):
+- Move detailed proofs to appendix
+- Condense related work (cite surveys instead of individual papers)
+- Combine similar experiments into unified tables
+- Use smaller figure sizes with subfigures
+- Tighten writing: eliminate redundancy, use active voice
+
+When expanding (e.g., ICML 8 → ICLR 9):
+- Add ablation studies reviewers requested
+- Expand limitations discussion
+- Include additional baselines
+- Add qualitative examples
+
+**Step 4: Conference-Specific Adjustments**
+
+| Target Venue | Required Additions |
+|--------------|-------------------|
+| **ICML** | Broader Impact Statement (after conclusion) |
+| **ICLR** | LLM usage disclosure, reciprocal reviewing agreement |
+| **ACL/EMNLP** | Limitations section (mandatory), Ethics Statement |
+| **AAAI** | Strict adherence to style file (no modifications) |
+| **NeurIPS** | Paper checklist (appendix), lay summary if accepted |
+
+**Step 5: Update References**
+
+```latex
+% Remove self-citations that reveal identity (for blind review)
+% Update any "under review" citations to published versions
+% Add new relevant work published since last submission
+```
+
+**Step 6: Addressing Previous Reviews**
+
+When resubmitting after rejection:
+- **Do** address reviewer concerns in the new version
+- **Do** add experiments/clarifications reviewers requested
+- **Don't** include a "changes from previous submission" section (blind review)
+- **Don't** reference the previous submission or reviews
+
+**Common Conversion Pitfalls:**
+- ❌ Copying `\usepackage` commands (causes conflicts)
+- ❌ Keeping old conference header/footer commands
+- ❌ Forgetting to update `\bibliography{}` path
+- ❌ Missing conference-specific required sections
+- ❌ Exceeding page limit after format change
+
+---
+
+## Citation Workflow (Hallucination Prevention)
+
+**⚠️ CRITICAL**: AI-generated citations are a high-risk failure mode. **Never write BibTeX from memory.**
+
+### Canonical authority
+
+Use `references/citation-workflow.md` as the default authority for citation verification.
+
+The default verification path is:
+1. **Search programmatically** with Semantic Scholar / CrossRef / arXiv / OpenAlex when appropriate.
+2. **Verify existence** in two sources when the claim is important.
+3. **Retrieve BibTeX programmatically** from DOI or a trusted source.
+4. **Validate the claim** against the actual paper content when the citation supports a specific statement.
+5. **Add the citation** only after the metadata and claim are verified.
+
+### The golden rule
+
+```text
+IF you cannot verify a citation programmatically:
+    -> mark it as [CITATION NEEDED] or [PLACEHOLDER - VERIFY]
+    -> tell the scientist explicitly
+    -> NEVER invent a plausible-sounding reference
+```
+
+### Workflow 2: Adding citations
+
+```text
+Citation verification:
+- [ ] Step 1: Search with Semantic Scholar / CrossRef / arXiv / OpenAlex as appropriate
+- [ ] Step 2: Confirm title, authors, year, and venue
+- [ ] Step 3: Retrieve BibTeX from DOI, arXiv, or another trusted export path
+- [ ] Step 4: Verify that the claim being cited actually appears in the source
+- [ ] Step 5: Add verified BibTeX to the bibliography
+- [ ] Step 6: If any step fails -> mark as placeholder and report it explicitly
+```
+
+### Discovery vs authority
+
+- **Programmatic APIs** are the canonical verification path.
+- **Google Scholar** may still be used as a manual discovery surface when coverage is weak, but not as the primary authority.
+- If Google Scholar finds something that the canonical APIs do not, treat it as a lead that still requires explicit verification.
+
+### Summary: citation rules
+
+| Situation | Action |
+|-----------|--------|
+| Verified metadata + verified BibTeX + verified claim | ✅ Use the citation |
+| Verified paper exists but the claim was not checked | ⚠️ Use only for general attribution, not for precise technical claims |
+| Discovery surface suggests a paper but metadata is still weak | ⚠️ Keep as lead, not as final citation |
+| Cannot verify programmatically | ❌ Mark `[CITATION NEEDED]`, inform the scientist |
+
+**🚨 NEVER generate BibTeX from memory. Use the programmatic workflow in `references/citation-workflow.md`. 🚨**
+
+### Complete Citation Workflow Example
+
+**Scenario**: You need to cite the Transformer paper.
+
+```text
+Step 1: Search programmatically
+- Semantic Scholar query: "Attention is All You Need Vaswani 2017"
+- Result: title, authors, year, and DOI align
+
+Step 2: Verify existence
+- CrossRef confirms DOI metadata
+- Semantic Scholar record matches the same paper
+
+Step 3: Retrieve BibTeX
+- Fetch BibTeX from the DOI / trusted export path
+
+Step 4: Verify the claim
+- Read the abstract or paper section that supports the cited statement
+- Confirm that the claim being cited is actually present
+
+Step 5: Add to bibliography
+- Paste verified BibTeX into the .bib file
+- Cite with the verified key
+
+Step 6: If any step fails
+- mark the citation as [PLACEHOLDER - VERIFY]
+- tell the scientist explicitly what remains unverified
+```
+
+---
+
+## Common Issues and Solutions
+
+**Issue: Abstract too generic**
+
+Delete first sentence if it could be prepended to any ML paper. Start with your specific contribution.
+
+**Issue: Introduction exceeds 1.5 pages**
+
+Split background into Related Work. Front-load contribution bullets. Methods should start by page 2-3.
+
+**Issue: Experiments lack explicit claims**
+
+Add sentence before each experiment: "This experiment tests whether [specific claim]..."
+
+**Issue: Reviewers find paper hard to follow**
+
+- Add explicit signposting: "In this section, we show X"
+- Use consistent terminology throughout
+- Include figure captions that stand alone
+
+**Issue: Missing statistical significance**
+
+Always include:
+- Error bars (specify: std dev or std error)
+- Number of runs
+- Statistical tests if comparing methods
+
+---
+
+## Reviewer Evaluation Criteria
+
+Reviewers assess papers on four dimensions:
+
+| Criterion | What Reviewers Look For |
+|-----------|------------------------|
+| **Quality** | Technical soundness, well-supported claims |
+| **Clarity** | Clear writing, reproducible by experts |
+| **Significance** | Community impact, advances understanding |
+| **Originality** | New insights (doesn't require new method) |
+
+**Scoring (NeurIPS 6-point scale):**
+- 6: Strong Accept - Groundbreaking, flawless
+- 5: Accept - Technically solid, high impact
+- 4: Borderline Accept - Solid, limited evaluation
+- 3: Borderline Reject - Solid but weaknesses outweigh
+- 2: Reject - Technical flaws
+- 1: Strong Reject - Known results or ethics issues
+
+See [references/reviewer-guidelines.md](references/reviewer-guidelines.md) for detailed reviewer instructions.
+
+---
+
+## Tables and Figures
+
+### Tables
+
+Use `booktabs` LaTeX package for professional tables:
+
+```latex
+\usepackage{booktabs}
+\begin{tabular}{lcc}
+\toprule
+Method & Accuracy ↑ & Latency ↓ \\
+\midrule
+Baseline & 85.2 & 45ms \\
+\textbf{Ours} & \textbf{92.1} & 38ms \\
+\bottomrule
+\end{tabular}
+```
+
+**Rules:**
+- Bold best value per metric
+- Include direction symbols (↑ higher is better, ↓ lower is better)
+- Right-align numerical columns
+- Consistent decimal precision
+
+### Figures
+
+- **Vector graphics** (PDF, EPS) for all plots and diagrams
+- **Raster** (PNG 600 DPI) only for photographs
+- Use **colorblind-safe palettes** (Okabe-Ito or Paul Tol)
+- Verify **grayscale readability** (8% of men have color vision deficiency)
+- **No title inside figure**—the caption serves this function
+- **Self-contained captions**—reader should understand without main text
+
+---
+
+## References & Resources
+
+### Reference Documents (Deep Dives)
+
+| Document | Contents |
+|----------|----------|
+| [writing-guide.md](references/writing-guide.md) | Gopen & Swan 7 principles, Ethan Perez micro-tips, word choice |
+| [citation-workflow.md](references/citation-workflow.md) | Citation APIs, Python code, BibTeX management |
+| [checklists.md](references/checklists.md) | NeurIPS 16-item, ICML, ICLR, ACL requirements |
+| [reviewer-guidelines.md](references/reviewer-guidelines.md) | Evaluation criteria, scoring, rebuttals |
+| [sources.md](references/sources.md) | Complete bibliography of all sources |
+| **Literature Research:** |
+| [arxiv-search-guide.md](references/literature-research/arxiv-search-guide.md) | arXiv search strategies, URL patterns, Chrome MCP automation |
+| [paper-quality-criteria.md](references/literature-research/paper-quality-criteria.md) | 5-dimension paper evaluation rubrics (innovation, method, experiments, writing, impact) |
+
+### LaTeX Templates
+
+Templates in `templates/` directory: **ICML 2026**, **ICLR 2026**, **NeurIPS 2025**, **ACL/EMNLP**, **AAAI 2026**, **COLM 2025**.
+
+**Compiling to PDF:**
+- **VS Code/Cursor**: Install LaTeX Workshop extension + TeX Live → Save to auto-compile
+- **Command line**: `latexmk -pdf main.tex` or `pdflatex` + `bibtex` workflow
+- **Online**: Upload to [Overleaf](https://overleaf.com)
+
+See [templates/README.md](templates/README.md) for detailed setup instructions.
+
+### Key External Sources
+
+**Writing Philosophy:**
+- [Neel Nanda: How to Write ML Papers](https://www.alignmentforum.org/posts/eJGptPbbFPZGLpjsp/highly-opinionated-advice-on-how-to-write-ml-papers) - Narrative, "What/Why/So What"
+- [Farquhar: How to Write ML Papers](https://sebastianfarquhar.com/on-research/2024/11/04/how_to_write_ml_papers/) - 5-sentence abstract
+- [Gopen & Swan: Science of Scientific Writing](https://cseweb.ucsd.edu/~swanson/papers/science-of-writing.pdf) - 7 reader expectation principles
+- [Lipton: Heuristics for Scientific Writing](https://www.approximatelycorrect.com/2018/01/29/heuristics-technical-scientific-writing-machine-learning-perspective/) - Word choice
+- [Perez: Easy Paper Writing Tips](https://ethanperez.net/easy-paper-writing-tips/) - Micro-level clarity
+
+**APIs:** [Semantic Scholar](https://api.semanticscholar.org/api-docs/) | [CrossRef](https://www.crossref.org/documentation/retrieve-metadata/rest-api/) | [arXiv](https://info.arxiv.org/help/api/basics.html)
+
+**Venues:** [NeurIPS](https://neurips.cc/Conferences/2025/PaperInformation/StyleFiles) | [ICML](https://icml.cc/Conferences/2025/AuthorInstructions) | [ICLR](https://iclr.cc/Conferences/2026/AuthorGuide) | [ACL](https://github.com/acl-org/acl-style-files)