This reference documents the mandatory checklist requirements for major ML/AI conferences. All major venues now require paper checklists—missing them results in desk rejection.
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## Contents
- [NeurIPS Paper Checklist](#neurips-paper-checklist)
All NeurIPS submissions must include a completed paper checklist. Papers lacking this element face **automatic desk rejection**. The checklist appears after references and supplemental material, outside the page limit.
### 16 Required Checklist Items
#### 1. Claims Alignment
Authors must verify that abstract and introduction claims match theoretical and experimental results, with clearly stated contributions, assumptions, and limitations.
**What to check:**
- [ ] Abstract claims match actual results
- [ ] Introduction doesn't overclaim
- [ ] Contributions are specific and falsifiable
#### 2. Limitations Discussion
Papers should include a dedicated "Limitations" section addressing strong assumptions, robustness to violations, scope constraints, and performance-influencing factors.
**What to include:**
- [ ] Dedicated Limitations section
- [ ] Honest assessment of scope
- [ ] Conditions where method may fail
#### 3. Theory & Proofs
Theoretical contributions require full assumption statements and complete proofs (main paper or appendix with proof sketches for intuition).
**What to check:**
- [ ] All assumptions stated formally
- [ ] Complete proofs provided (main text or appendix)
- [ ] Proof sketches for intuition in main text
#### 4. Reproducibility
Authors must describe steps ensuring results verification through code release, detailed instructions, model access, or checkpoints appropriate to their contribution type.
**What to provide:**
- [ ] Clear reproducibility statement
- [ ] Code availability information
- [ ] Model checkpoints if applicable
#### 5. Data & Code Access
Instructions for reproducing main experimental results should be provided (supplemental material or URLs), including exact commands and environment specifications.
All existing assets require creator citations, license names, URLs, version numbers, and terms-of-service acknowledgment.
**What to document:**
- [ ] Dataset licenses cited
- [ ] Code licenses respected
- [ ] Version numbers included
#### 13. Asset Documentation
New releases need structured templates documenting training details, limitations, consent procedures, and licensing information.
**For new datasets/models:**
- [ ] Datasheet or model card
- [ ] Training data documentation
- [ ] Known limitations
#### 14. Human Subjects
Crowdsourcing studies must include participant instructions, screenshots, compensation details, and comply with minimum wage requirements.
**What to include:**
- [ ] Task instructions
- [ ] Compensation details
- [ ] Time estimates
#### 15. IRB Approvals
Human subjects research requires documented institutional review board approval or equivalent, with risk descriptions disclosed (maintaining anonymity at submission).
**What to verify:**
- [ ] IRB approval obtained
- [ ] Risk assessment completed
- [ ] Anonymized at submission
#### 16. LLM Declaration
Usage of large language models as core methodology components requires disclosure; writing/editing use doesn't require declaration.
Authors select "yes," "no," or "N/A" per question, with optional 1-2 sentence justifications.
**Important:** Reviewers are explicitly instructed not to penalize honest limitation acknowledgment.
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## ICML Paper Checklist
### Broader Impact Statement
ICML requires a Broader Impact Statement at the end of the paper, before references. This does NOT count toward the page limit.
**Required elements:**
- Potential positive impacts
- Potential negative impacts
- Mitigation strategies
- Who may be affected
### ICML Specific Requirements
#### Reproducibility Checklist
- [ ] Data splits clearly specified
- [ ] Hyperparameters listed
- [ ] Search ranges documented
- [ ] Selection method explained
- [ ] Compute resources specified
- [ ] Code availability stated
#### Statistical Reporting
- [ ] Error bars on all figures
- [ ] Standard deviation vs standard error specified
- [ ] Number of runs stated
- [ ] Significance tests if comparing methods
#### Anonymization
- [ ] No author names in paper
- [ ] No acknowledgments
- [ ] No grant numbers
- [ ] Prior work cited in third person
- [ ] No identifiable repository URLs
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## ICLR Requirements
### LLM Disclosure Policy (New for 2026)
ICLR has a specific LLM disclosure requirement:
> "If LLMs played a significant role in research ideation and/or writing to the extent that they could be regarded as a contributor, authors must describe their precise role in a separate appendix section."
**When disclosure is required:**
- LLM used for significant research ideation
- LLM used for substantial writing
- LLM could be considered a contributor
**When disclosure is NOT required:**
- Grammar checking
- Minor editing assistance
- Code completion tools
**Consequences of non-disclosure:**
- Desk rejection
- Potential post-publication issues
### ICLR Specific Requirements
#### Reproducibility Statement (Optional but Recommended)
Add a statement referencing:
- Supporting materials
- Code availability
- Data availability
- Model checkpoints
#### Ethics Statement (Optional)
Address potential concerns in ≤1 page. Does not count toward page limit.
#### Reciprocal Reviewing
- Authors on 3+ papers must serve as reviewers for ≥6 papers
- Each submission needs ≥1 author registered to review ≥3 papers
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## ACL Requirements
### Limitations Section (Mandatory)
ACL specifically requires a Limitations section:
**What to include:**
- Strong assumptions made
- Scope limitations
- When method may fail
- Generalization concerns
**Important:** The Limitations section does NOT count toward the page limit.
