mlsys-related-work
Use when positioning an MLSys submission against the fast-moving ML-systems literature scattered across OSDI, SOSP, NSDI, ASPLOS, and ML venues, handling arXiv-first and open-source-first prior work, comparing against production systems that have no paper, and writing the delta statement two reviewer cultures will both accept.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mlsys-related-work --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# MLSys Related Work Use this to audit positioning and novelty. The core difficulty is that MLSys's literature does not live at MLSys: the field's landmark systems are spread across OS, architecture, networking, and ML conferences, plus arXiv reports and repositories that never became papers. A related-work section here is judged on whether it maps that whole territory, not one venue's proceedings. ## The five lanes to cover | Lane | Where it publishes | What reviewers check | |---|---|---| | ML-systems venue work | MLSys proceedings (proceedings.mlsys.org) | Do you know this venue's own line on your topic? | | Classical systems venues | OSDI, SOSP, NSDI, ASPLOS, ATC, EuroSys, SC | Is the nearest big-venue system compared or distinguished? | | ML algorithm venues | NeurIPS, ICML, ICLR | Does the ML-side idea you accelerate/serve already have algorithmic competitors? | | Industry systems | arXiv reports, engineering blogs, open-source repos | Are the systems practitioners actually use acknowledged? | | Benchmarks/measurement | MLPerf/MLCommons line, characterization studies | Is your evaluation methodology situated, not invented? | A bibliography drawing on only one or two lanes sig
- The five lanes to cover
- The freshness problem
- Comparing against work without papers
- Writing the delta statement
- Building the capability table honestly
- Misattribution traps
- Scoping the search itself
- Double-blind interaction
- Output format
What does the mlsys-related-work skill do?
Use when positioning an MLSys submission against the fast-moving ML-systems literature scattered across OSDI, SOSP, NSDI, ASPLOS, and ML venues, handling arXiv-first and open-source-first prior work, comparing against production systems that have no paper, and writing the delta statement two reviewer cultures will both accept.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mlsys-related-work --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.