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Lemonade Review Guidelines

License: CC BY-SA 4.0 Commit Activity

About

The New Lemonade Review is a paper review list maintained by prospective and current PhD students @pku-lemonade/phds at LEMONADE, Peking University. It is intended to provide a comprehensive overview of the quintessential research ideas in the field of computer architecture and systems.

How to find the papers?

Important

Choose one of the first three strategies as your focus each week, depending on your current research needs.

Important

Check arXiv every day to make it a regular habit!

  • Goal: Get a broad overview of the topic.
  • Method: Search in Google Scholar or read survey papers.
  • Pace: 5+ papers/week (mostly skimming).
  • Goal: Understand a key researcher's approach (methods, presentation, evaluation).
  • Method: Search the author's papers in DBLP.
  • Pace: 2-5 papers/week (skim first, then carefully read relevant papers).

Citation Chasing

  • Goal: Deep dive into a core paper (e.g., your intended main baseline).
  • Method: Follow its main baselines/references (backward look) and check papers that cite it (forward look).
  • Pace: 2-3 papers/week (requires careful reading).
  • [!NOTE] Aim for at least 2 papers/week as you typically need to read the core paper alongside its main baseline.

arXiv Monitoring

What papers should be included?

  • Peer-reviewed full papers ONLY.
  • NO workshop papers, posters, or abstracts.
  • Preprints are okay only for LLM-related topics.

Important

Ensure that at least half the papers are either published in CCF Rank A venues, or have a relavance score at least 3.

How to organize the papers?

Format

  • Sort papers by year in each subsection.
  • CSV: Use quotes (" ") around titles and tags containing commas ","
  • PR Title/Description: Include search strategy, keywords, and note any papers read carefully (as opposed to skimmed).

Authors

  • Use the affiliation of the corresponding author (or last author).
  • Use standard, globally recognized abbreviations for affiliations.

Subsections

  • Put papers only in Level 3 or Level 4 subsections.
  • Group papers by a common challenge in each subsection. Briefly state that challenge at the beginning of the subsection.
  • Min 2 papers per subsection. If only one fits, find a partner paper, or connect this paper to a related subsection.
  • Max 5 papers per subsection. If more fit, split the subsection.

Tags

  • Use specific tags for key techniques or contributions, such as "xxx algorithm", "yyy model", "zzz architecture", etc.
  • Don't use broad area tags ("performance" or "architecture").
  • Don't use vague feature tags ("expresiveness", "scalability", "efficiency")unless combined with a specific technique (e.g., "xxx algorithm for scalability").
  • Explain potentially unclear acronyms ("XYZ framework") in tags.
  • Link related subsections (e.g., link hardware papers to related software papers sharing an idea, link compiler papers to related system papers sharing a technique).

How to read the papers? (Review Scores)

Presentation

Tip

Skimming: Title, Abstract, Introduction, Figures.

  • 5: Definitely stealing some ideas for how they explained things or made their figures. I wish my papers looked this good.
  • 4: I will take note a figure or explanation and use in my next paper.
  • 3: I can write as good as it.
  • 2: Kind of a pain to read, or the figures are confusing/ugly. Hard to tell what's going on easily.

Evaluation

Tip

Skimming: Experiments, Results, Reproducibility.

  • 5: Solid real-world tests. NVDA could actually use or bet on.
  • 4: Solid tests with real hardware. But the setup is not real-wrold ready.
  • 3: Okay tests with open source simulators. The results aren't obviously wrong.
  • 2: Okay tests with close source simulators. The results aren't obviously wrong.
  • 1: The results just don't make sense.

Novelty

Note

Requires careful reading: Assessing novelty means comparing the paper critically to related work. If you only skimmed the paper, either skip this score or assign at most 2.

  • 5: Totally new idea; groundbreaking.
  • 4: New take on existing ideas, or combines them smartly.
  • 3: An existing idea applied to a new area/topic.
  • 2: An existing idea applied to the same problem with standard incremental contributions.
  • 1: An existing idea applied to the same problem with minor variations.

Relevance

Note

Don't put the score in the review record because this score should be personal.

  • 5: Everyone need to read this paper
  • 4: I will put this paper on my side when I write my next paper
  • 3: I will cite this paper in my next paper
  • 2: I will cite this paper in my next survey paper