技能 数据科学 AISTATS审稿流程指南

AISTATS审稿流程指南

v20260724
aistats-review-process
本指南详细介绍了AISTATS的学术论文同行评审流程,涵盖了从OpenReview提交工作流到作者-审稿人互动、决策标准(正确性、意义、实证支持)等全方位知识点。它旨在帮助研究人员制定优化的投稿和回复策略,提升在统计学和机器学习领域的投稿成功率。
获取技能
368 次下载
概览

AISTATS Review Process

Use this to reason about review-stage strategy. Reopen the current CFP, OpenReview group, author instructions, reviewer instructions if posted, and code of conduct before making process claims.

Process model

  • AISTATS uses OpenReview for submission and review workflow in recent cycles.
  • Reviewers evaluate technical correctness, statistical and machine-learning contribution, empirical support, clarity, reproducibility, and relevance to artificial intelligence and statistics.
  • Author discussion is limited. AISTATS 2026 used a discussion period after initial reviews, with text-only author-reviewer discussion and no links.
  • Reviewer and author obligations include confidentiality, appropriate conflicts, professional conduct, and respect for anonymity.
  • The most useful response is a decision-focused clarification that gives the area chair or meta-reviewer a clean rationale for acceptance or rejection.
  • Accepted papers are published in PMLR, so final metadata and camera-ready compliance matter as much as the initial acceptance.

Who reviews here

  • The pool mixes ML researchers with statisticians and statistical learning theorists; expect at least one reviewer to read proofs and assumption sets line by line.
  • Because AISTATS is smaller and more specialized than NeurIPS or ICML, topical matches are closer, so vague proof sketches get caught rather than skimmed past.
  • Borderline theory-plus-experiments papers usually fall on one of three edges: an assumption the experiments do not satisfy, a missing classical-statistics baseline, or a rate claim never checked empirically.

Scoring leverage table

Review dimension What raises it What sinks it
Correctness Complete assumption statements with a main-text proof sketch Hidden conditions; constants swept into O-notation when they matter
Significance A guarantee the ML literature lacked, or a practical method statistics lacked Incremental rate gain with no conceptual or practical payoff
Empirical support Experiments engineered to probe the theory Benchmarks disconnected from the theorem regimes
Clarity Numbered assumptions and a single notation source Notation collisions between sections

Stage-by-stage realism

  • Initial reviews: triage by what the meta-reviewer would weigh, not by reviewer tone.
  • Discussion: windows are short; an early, precise reply is worth more than a late comprehensive one.
  • Decision: the meta-review synthesizes; one unanswered correctness objection outweighs several resolved clarity complaints.
  • Reviewer-volunteer expectations for submitting authors have appeared in recent cycles; confirm the current CFP rather than assuming either way.

Output format

[Current stage] submitted / reviews / discussion / decision / camera-ready
[Decision actors] <reviewers/meta-reviewer/chairs>
[Likely leverage] <correctness/statistics/experiments/clarity/reproducibility>
[Forbidden moves] <identity leak / external links if forbidden / new unsupported results>
[Next response move] <one action>
信息
Category 数据科学
Name aistats-review-process
版本 v20260724
大小 3.38KB
更新时间 2026-07-28
语言