Skill UI

A comprehensive guide for revising technical papers submitted to ACM Multimedia (ACM MM). It teaches authors how to shift focus from single-modality benchmarks to cross-modal fusion mechanisms, ensuring all media elements (figures, audio, video) function as direct evidence. The guide emphasizes structuring the argument within a tight 6-8 page conference limit, making the multimedia contribution visible from page one.

A comprehensive pre-upload audit checklist for submitting papers to the CoRL (Conference on Robot Learning). This guide details specific requirements for the submission package, including the mandatory 8-page limit (which must account for a dedicated Limitations section), adherence to double-anonymous rules, and detailed sweeps for preserving author and lab anonymity in text, figures, and videos. Essential for ensuring compliance with complex conference guidelines.

A comprehensive guide detailing the submission rules and best practices for supplementary materials, including videos, appendices, code, and data, for top-tier robotics conferences. It outlines distinct submission channels, strict technical requirements (e.g., 250MB video cap, anonymity), and the necessary transition steps from the review phase to the final camera-ready publication format.

A comprehensive guide for authors submitting to computer vision conferences, detailing how to structure, organize, and utilize supplementary material. It clearly distinguishes between core claims (which must be in the main body) and supportive evidence, such as full ablation grids, detailed derivations, and video results, which belong in the supplement. The guide covers best practices for handling anonymity, video evidence, and avoiding common submission bugs.

A comprehensive guide for positioning and refining computer vision manuscripts for the IEEE/CVF International Conference on Computer Vision (ICCV). This skill helps authors assess conference fit, structure evidence, perform benchmarking, and adopt the necessary narrative for a flagship CV submission, covering topics from foundation models to video recognition.