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research-methodology

伊森·佩雷斯的经验之谈：实证对齐研究的核心要点——速度、实验、协作

SKILL.md
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name: research-methodology
description: Ethan Perez's tips for empirical alignment research - velocity, experimentation, collaboration

Research Methodology: Tips for Empirical Alignment Research

Based on Ethan Perez's post. Applies to highly experimental LLM alignment research (scalable oversight, adversarial robustness, chain-of-thought faithfulness, process-based oversight, model organisms of misalignment).

Core Principles

1. Hard Work Pays Off

  • •Run as many experiments as you can, tinker a lot, try lots of stuff
  • •Often many reasonable-sounding ideas need testing—sometimes the 5th or 20th thing is what works
  • •"Rich get richer" effect: the more you experiment, the better you get at picking the right experiments
  • •More things work when you try more stuff → easier to stay motivated

2. Rapid Iteration (Velocity)

  • •Reduce uncertainty at the fastest possible rate (Jacob Steinhardt)
  • •Get quick feedback and iterate on ideas rapidly
  • •With LLMs, you can reduce uncertainty really quickly—even with a single message to GPT-4/Claude
  • •Can gain 1+ OOMs more information per unit time by derisking ideas in the quickest way possible

3. Avoid the "Swamp"

  • •The swamp = getting stuck when you really want technique X to work but nothing succeeds
  • •Solution: high velocity—test as many ideas as possible per unit time until you escape
  • •For LLM research: you should rarely be stuck in a swamp
    • •If stuck → you've likely exhausted low-hanging fruit on that problem/approach
    • •There's other low-hanging fruit elsewhere—go pick that instead

4. Low-Hanging Fruit Abundance

  • •The field is moving so quickly that there's much more low-hanging fruit than almost any other field
  • •Each new model capability = time to be opportunistic, explore what's now possible
  • •High velocity is useful for both:
    • •Picking low-hanging fruit quickly
    • •Getting through swamps when you must solve a particular problem

Collaboration & Communication

Strong Collaborator Qualities

Ethan puts 70% weight on "getting ideas to work quickly" as criteria. Other qualities:

  • •Receptive to feedback
  • •Adds emotional energy rather than draining it
  • •Transparent/communicative about issues faced
  • •High-trust relationship where various topics can be discussed easily
  • •Notices and calls out room for improvement in collaboration

Communication Best Practices

  • •Overcommunicate: bring up issues during meetings or privately—nip problems in the bud
  • •Close mentorship is maybe the fastest path to become an expert in a domain
  • •Take agency: organize coworking, discussion groups, standups—whatever helps
  • •Get feedback from peers, iterate on project plans

Research Workflow

  • •Have a clear project plan with motivation and research goals
  • •List all experiments you can think of running
  • •Think about milestones and deliverables to stay accountable
  • •Know what tools are available—sharing tooling increases experimental velocity

Paper Writing

  • •See ethanperez.net/easy-paper-writing-tips/ for ML paper writing tips
  • •Write short paragraphs composed of short sentences
  • •Write comprehensive abstracts
  • •Seek feedback from a naive audience
  • •Distinguish confirmation from exploration in your writeup

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