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AlvaroBiano
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research-paper-writing

Coordinate ML/AI paper development from design to submission across conference workflows.

Updated May 2, 2026
Search Tags:#citations#pipeline#reproducibility#experimentation#research-writing#autoreason
One-click install
npx skills add https://github.com/AlvaroBiano/hermes-agent --skill research-paper-writing-alvarobiano
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-paper-writing
Source: https://github.com/AlvaroBiano/hermes-agent/tree/main/skills/research/research-paper-writing
Command: npx skills add https://github.com/AlvaroBiano/hermes-agent --skill research-paper-writing-alvarobiano

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides an end-to-end pipeline for producing publication-ready ML/AI research papers, guiding the entire lifecycle from design and experiments to drafting, review, and submission, while enforcing a coherent narrative and rigorous documentation.

Core Features & Use Cases

  • End-to-end research workflow: design, execute experiments, analyze results, draft sections, and prepare submission-ready manuscripts.
  • Iterative refinement: supports structured revision cycles, external critique, and evidence-backed updates to claims.
  • Reproducibility & reporting: standardized logs, checklists, and provenance for methods, data, and results to ease reproducibility and reviewer scrutiny.

Quick Start

Initiate a new research project with the pipeline and begin at Phase 0: Project Setup.

Frequently Asked Questions about research-paper-writing

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

FAQPage Schema
How do I structure an ML research paper for NeurIPS or ICML submission?▼

Structure an ML research paper using an iterative refinement pipeline that coordinates design, experimentation, drafting, and submission, specifically enforcing reproducibility and evidence-backed claims for NeurIPS, ICML, and ICLR workflows.

What is the best way to ensure reproducibility in machine learning experimentation?▼

Ensure reproducibility in machine learning experimentation by applying standardized logs, checklists, and provenance tracking for methods, data, and results to withstand reviewer scrutiny during publication.

Can I use arxiv and semanticscholar citations for an automated research-writing pipeline?▼

Yes, an automated research-writing pipeline can use arxiv and semanticscholar citations, coordinating references and evidence to support structured documentation and iterative claim refinement for publication-ready manuscripts.

How do I manage iterative refinement cycles when drafting an AI research paper?▼

Manage iterative refinement cycles in AI research paper drafting by applying structured revision processes that incorporate external critique, update claims with evidence, and coordinate experiment logs for review-ready deliverables.

Does this research paper pipeline support formatting for AAAI and ACL workflows?▼

Yes, the research paper pipeline supports formatting and workflow coordination for AAAI and ACL, guiding the lifecycle from project setup to submission while maintaining a coherent narrative.

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