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research-paper-writing

Guides end-to-end ML research paper production from experiment design through conference submission.

Updated Sep 20, 2026
Search Tags:#machine learning#experiment design#citations#latex#research paper#neurips#conference submission
One-click install
npx skills add https://github.com/GreenyZA/neo-light --skill research-paper-writing-greenyza
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-paper-writing
Source: https://github.com/GreenyZA/neo-light/tree/main/.hermes-home/skills/research/research-paper-writing
Command: npx skills add https://github.com/GreenyZA/neo-light --skill research-paper-writing-greenyza

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires semanticscholar, arxiv, habanero, requests, scipy, numpy, matplotlib, SciencePlots, and includes references (resource) and assets (resource) components.

What problem does it solve? Writing a publication-ready ML/AI paper involves coordinating literature review, experiment design, statistical analysis, LaTeX drafting, citation verification, and venue-specific submission requirements — a process where missed steps (hallucinated citations, missing checklists, weak baselines) cause desk rejections. ## Core Features & Use Cases - Full Research Lifecycle Pipeline: Eight iterative phases covering project setup, literature review, experiment design, execution monitoring, statistical analysis, drafting, self-review, and submission for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. - Citation Hallucination Prevention: Mandatory 5-step verification workflow using Semantic Scholar, CrossRef, and arXiv APIs with programmatic BibTeX retrieval via DOI content negotiation. - Venue Templates & Checklists: Official LaTeX templates for six conferences plus pre-submission checklists covering page limits, NeurIPS 16-item checklist, ICLR LLM disclosure, and ACL limitations requirements. - Use Case: A researcher with experimental results asks the agent to draft an ICML submission — the skill verifies all citations programmatically, generates booktabs tables with error bars, applies the icml2026 template, and runs a simulated reviewer pass before submission. ## Quick Start Ask the agent to help write a research paper from your experiment results, specifying the target venue such as NeurIPS or ICML.

Frequently Asked Questions about research-paper-writing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a machine learning paper for NeurIPS or ICML?▼

Follow an iterative pipeline: define a one-sentence contribution, map every experiment to a claim, run baselines with statistical significance tests, then draft using the official venue LaTeX template. Finish with a simulated self-review and the venue's mandatory checklist before submitting.

How do I prevent AI-generated hallucinated citations in research papers?▼

Never generate BibTeX from memory — fetch it programmatically via DOI content negotiation from CrossRef. Verify each paper exists in at least two sources (Semantic Scholar plus arXiv or CrossRef) and confirm the cited claim actually appears in the paper's abstract.

What LaTeX templates are included for conference submissions?▼

Official templates are provided for ICML 2026, ICLR 2026, NeurIPS 2025, ACL, AAAI 2026, and COLM 2025, each with the correct style file, bibliography style, and example document. Page limits range from 7 pages (AAAI) to 9 pages (ICLR, NeurIPS, COLM).

Does the NeurIPS paper checklist cause desk rejection if missing?▼

Yes, NeurIPS submissions lacking the completed 16-item paper checklist face automatic desk rejection. The checklist covers claims alignment, limitations, reproducibility, statistical significance, compute resources, ethics, and LLM usage declaration, and appears after references outside the page limit.

How do I design human evaluation for NLP research papers?▼

Define evaluation dimensions, write annotation guidelines with examples, run a pilot to check inter-annotator agreement, then scale up. Report annotator count, Krippendorff's alpha or Cohen's kappa, compensation rate, and use pairwise comparisons rather than Likert scales for LLM output evaluation.

When should I use iterative refinement versus single-pass generation for paper drafts?▼

Use autoreason-style iterative refinement for mid-tier models on constrained tasks, where the generation-evaluation gap is largest. Frontier models on unconstrained tasks do better with critique-and-revise or single passes, since unconstrained iteration causes synthesis drift and fails to converge.

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