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CIKM Peer Review Navigator

brycewang-stanfordbybrycewang-stanford
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Learning & Documentation

Guides researchers through the ACM CIKM double-blind peer review pipeline, multi-community reviewer expectations, track criteria, and review packet decoding.

The CIKM Peer Review Navigator skill equips researchers with specialized guidance for the ACM CIKM peer review lifecycle hosted on EasyChair. It helps authors address the unique tri-lane reviewer pool spanning Information Retrieval, Data Mining, and Knowledge Management/Databases, evaluate submissions against distinct track rubrics (Full, Short, Applied, Resource, Demo), decode lane-specific reviewer feedback, and stay compliant with ACM peer review policies and tight camera-ready turnarounds.

Key Features

01Tri-lane reviewer analysis across Information Retrieval, Data Mining, and Knowledge Management standards
02Review packet decoding framework to differentiate lane bias from blocking technical flaws
03Borderline decision dynamics and program chair calibration insights
041,074 GitHub stars
05Track-specific evaluation breakdown for Full, Short, Applied, Resource, and Demo papers
06ACM Peer Review Policy guidance covering double-blind compliance and camera-ready milestones

Use Cases

01Decoding CIKM review packets to prioritize responses or refine papers for camera-ready submission
02Extracting routing signals from rejected submissions to target optimal fallback venues
03Performing pre-submission self-audits against multi-community reviewer expectations and track criteria