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LamseyahElias
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research-paper-writing

Guide ML research projects from literature review to paper submission.

Updated Jun 11, 2026
Search Tags:#reproducibility#literature-review#experiment-design#paper-writing#research-paper-writing#end-to-end-workflow
One-click install
npx skills add https://github.com/LamseyahElias/jarvis-cloud-v2 --skill research-paper-writing-lamseyahelias
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-paper-writing
Source: https://github.com/LamseyahElias/jarvis-cloud-v2/tree/main/hermes-agent/skills/research/research-paper-writing
Command: npx skills add https://github.com/LamseyahElias/jarvis-cloud-v2 --skill research-paper-writing-lamseyahelias

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires semanticscholar, arxiv, habanero, requests, scipy, numpy, matplotlib, SciencePlots.

What problem does it solve?

Enable an end-to-end workflow to turn ML research ideas into publication-ready papers.

Core Features & Use Cases

  • End-to-end research workflow from project setup, literature review, experiment design, execution, analysis, to writing and submission.
  • Phase-by-phase guidance, reproducibility templates, and review-ready artifacts that streamline collaboration among authors.
  • Supports best-practice norms for reproducibility, data provenance, statistical reporting, and experiment monitoring.

Quick Start

Initiate a new paper project by outlining the contribution, aligning on scope, and following the Phase 0–Phase 4 steps to produce a complete draft ready for review.

Frequently Asked Questions about research-paper-writing

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

FAQPage Schema
How do I manage an end-to-end machine learning paper writing workflow?▼

Reproducibility in ML research is supported through structured templates, data provenance tracking, statistical reporting, and experiment monitoring. These ensure rigorous evaluation and review-ready artifacts throughout the writing pipeline.

How do I conduct a literature review for an ML research paper?▼

Conducting a literature review for an ML research paper involves systematically searching and analyzing prior work. The workflow provides phase-by-phase guidance leveraging sources like arXiv and Semantic Scholar to align your contribution and scope.

Can I use this workflow for submission to NeurIPS, ICML, or ACL?▼

Yes, you can use this workflow for submission to major venues like NeurIPS, ICML, ICLR, ACL, and COLM. It provides structured processes and review-ready artifacts tailored to meet the standards of these conferences.

Does this research paper workflow integrate with arXiv and Semantic Scholar?▼

The workflow uses NumPy, SciPy, and Matplotlib to support experiment design and data analysis. It provides reproducibility templates and monitoring to ensure rigorous statistical reporting and review-ready artifacts.

What is the best way to structure experiment design for a publication-ready paper?▼

The best way to structure experiment design for a publication-ready paper is to follow a phase-by-phase guide that includes reproducibility templates and statistical reporting. This ensures rigorous evaluation across all designed experiments.

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