CoRL Related Work Writing Assistant
Guides the structuring, positioning, and citation hygiene of related work sections for Conference on Robot Learning (CoRL) submissions.
Designed specifically for robot learning researchers targeting the Conference on Robot Learning (CoRL), this skill guides the positioning of academic papers across multiple overlapping fields. It ensures comprehensive literature coverage across the robot-learning lineage (CoRL, RSS, ICRA), core ML methodologies (NeurIPS, ICLR, ICML), foundation-model/VLA trends, and classical robotics baselines. With built-in guidelines for handling preprint velocity, double-anonymous self-citations, and PMLR volume-year offset traps, it helps authors avoid common reviewer pitfalls and craft ironclad related work sections.
主な機能
01Prevents PMLR citation errors, including volume-year offset and venue misattribution
02Ensures double-anonymous peer-review compliance for self-citations
03Structures literature reviews across robot learning, ML methods, and classical robotics
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05Provides strategies for handling concurrent preprints and fast-moving VLA literature
06Includes a pre-submission section audit checklist for citation breadth and baseline alignment
ユースケース
01Positioning a novel robot learning paper across classical, ML, and modern VLA literature
02Handling concurrent arXiv preprints and double-anonymous self-citations safely
03Auditing citations to fix PMLR bibliography errors and verify venue attribution