colm-related-work
De la autor
Use when positioning a COLM paper inside the fastest-moving literature in ML — triaging arXiv-heavy citations, handling concurrent work fairly, citing model and dataset artifacts correctly, distinguishing COLM's three-edition archive from adjacent venues' archives, and keeping self-citation double-blind safe.
Instalare
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colm-related-work -a claude-code
Se instalează în .claude/skills/colm-related-work/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
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De ce 88
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- acl-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning an ACL submission against the NLP literature, covering ACL Anthology citation practice, arXiv-versus-published version citation, concurrent LLM-era preprints, prior-cycle ARR resubmission overlap, anonymity-preserving self-citation, and the fast-moving baseline problem in computational linguistics.Știință★ 1.3K
- colt-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a COLT (Conference on Learning Theory) submission against prior bounds and models — building the known-versus-new comparison across COLT/ALT lineage, STOC/FOCS, NeurIPS-and-ICML theory tracks, statistics journals, and arXiv concurrency, while respecting anonymity and the parallel-submission rules.Știință★ 1.3K
- imc-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when writing or auditing the related-work and positioning of an ACM IMC paper, covering the measurement literature lanes, positioning against prior datasets and vantage points, delta-first framing, citing the datasets and tools you build on, distinguishing IMC from SIGCOMM/NSDI/PAM prior art, and keeping self-citations double-blind.Știință★ 1.3K
- kdd-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a KDD submission against the data-mining lineage (prior KDD volumes, ICDM, SDM, WSDM, CIKM, WWW) and the ML flagships, handling venue misattribution traps, cross-cycle resubmission overlap, concurrent arXiv work, and the mechanism-contrast style of novelty argument that ACM SIGKDD reviewers expect.Știință★ 1.3K
- uai-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a UAI submission within the probabilistic reasoning, graphical-model, causality, and Bayesian ML literature, covering PMLR archival status of recent UAI volumes, double-blind self-citation discipline, concurrent arXiv and workshop versions, and the cross-community citation coverage UAI reviewers check first.Știință★ 1.3K
- cikm-related-workbrycewang-stanford/Awesome-Journal-SkillsUse when positioning a CIKM submission against three literatures at once — retrieval, mining, and knowledge management/databases — building the boundary-work paragraph, guarding against misattributing SIGIR/KDD/ICDM classics to CIKM, and handling preprints under the arXiv-declaration and dual-submission rules.Știință★ 1.3K
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