mlsys-topic-selection
Use when deciding whether a project belongs at MLSys rather than OSDI, SOSP, NSDI, ASPLOS, ATC, EuroSys, or the ML conferences, testing for genuine ML-systems co-design, choosing between the research and industrial tracks, and sharpening the systems-for-ML or ML-for-systems framing before writing starts.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mlsys-topic-selection --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 Topic Selection Use this before writing begins. MLSys exists for work where machine learning and computer systems constrain each other — the CFP spans **systems for ML** (training, inference, serving, compilers, runtimes, specialized hardware, hardware-efficient methods, benchmarks and tooling) and **ML for systems** (learned scheduling, LLM-driven hardware design and system optimization), plus adjacent lanes like federated learning, compound AI and agent systems, privacy/security for ML, and data preparation (2026 topics list, verified 2026-07-08). Fit failures here are usually routing failures: strong work aimed at the wrong reviewer pool. ## The co-design test Ask two questions; MLSys wants both answers to be yes. 1. Does an ML property (model structure, training dynamics, tolerance to approximation, request patterns of ML workloads) shape the system design? 2. Does a systems property (memory hierarchy, interconnect, scheduling, cost) shape the ML method or its evaluation? One yes is a re-routing signal: pure systems novelty exercised on an ML workload belongs at a general systems venue; pure ML novelty measured for speed belongs at an ML venue. ## Routing table | Projec
- The co-design test
- Routing table
- Signals your project is MLSys-shaped
- Track choice within MLSys (2026 structure)
- Sharpening moves before committing
- Vignette: three borderline projects, routed
- Anti-patterns that fail the fit test
- Output format
What does the mlsys-topic-selection skill do?
Use when deciding whether a project belongs at MLSys rather than OSDI, SOSP, NSDI, ASPLOS, ATC, EuroSys, or the ML conferences, testing for genuine ML-systems co-design, choosing between the research and industrial tracks, and sharpening the systems-for-ML or ML-for-systems framing before writing starts.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mlsys-topic-selection --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.