Skill UI

This guide helps researchers determine the most appropriate top-tier academic conference (e.g., CoNEXT, SIGCOMM, NSDI, IMC) and submission cycle for their networking research. It provides detailed criteria, routing tables, and tests (e.g., platform-realism test, model-swap test) to ensure the contribution is evaluated on a real target and fits the target community's scope and rigor.

This guide helps researchers determine if their embodied AI or robotics project is best suited for the Conference on Robot Learning (CoRL). It provides a rigorous two-axis test—assessing if learning is the core contribution and if embodiment is essential to the claim—to decide between submitting to CoRL, ICRA, IROS, NeurIPS, or other journals.

A comprehensive guide for computer vision researchers on strategically positioning their work. It helps assess whether the core contribution is related to visual data or visual computation, providing fit tests and a routing map to recommend the most appropriate top-tier conferences (CVPR, ICCV, NeurIPS) or journals based on the contribution type and technical maturity.

A comprehensive guide for researchers deciding the optimal conference venue for their NLP project. It analyzes whether a project is best suited for EACL, ACL, EMNLP, NAACL, or other specialized venues (like LREC-COLING or COLM). The guide considers scope, contribution type (e.g., analysis vs. new system), temporal constraints, and the trade-offs between long and short paper formats.

This guide helps researchers determine the optimal academic conference (ECAI, IJCAI, AAAI, etc.) for their AI contribution *before* starting to write. It provides structured tests (like the Model-swap test and General-audience test) and criteria (contribution shape, main track vs. application) to ensure the work is optimally matched to a specialized venue, maximizing the chances of acceptance and impact.

This comprehensive guide outlines a detailed, backward-planning workflow for submitting research papers to major AI conferences like ECAI or IJCAI-ECAI. It covers the entire academic lifecycle, from initial topic selection and evidence type planning to abstract submission, full paper drafting, rebuttal response, and final camera-ready publication, ensuring authors meet strict deadlines and adhere to rigorous review standards.

A comprehensive guide for computer vision researchers to determine if their project is a good fit for ECCV, considering scope, technical durability, and academic timing. It weighs the project's contribution against the specific requirements of ECCV versus competing top-tier venues like CVPR and ICCV, ensuring strategic submission planning.

This guide helps researchers determine the optimal venue for their database project, analyzing whether the work belongs at EDBT, SIGMOD, VLDB, ICDE, or a dedicated theory venue like ICDT. It provides frameworks for choosing the right conference based on contribution type (systems, theory, experiments), open access preferences, and submission cycle proximity.

This comprehensive guide assists authors in strategically positioning their computer vision manuscripts for the European Conference on Computer Vision (ECCV). It covers conference fit assessment, manuscript re-framing, required evidence (e.g., ablations, baselines, failure modes), and structural advice to ensure the work aligns with ECCV's scope and current review policies. Use this tool for venue selection and submission preparation.

A comprehensive guide for researchers deciding the optimal conference venue (e.g., FAST, OSDI, NSDI, ATC) for their storage-related academic work. It advises on distinguishing a core storage contribution from general systems results, detailing specific contribution shapes FAST rewards, and providing routing logic based on the project's nature and evidence maturity.

This guide provides a comprehensive project management workflow for submitting research to the USENIX FAST conference. It covers the entire academic lifecycle, detailing milestones from initial topic selection and evidence locking to double-blind submission, author response, and managing the complex two-deadline cycle, including potential one-shot revisions. Use this to back-plan your research schedule based on concrete storage measurement timelines.

This guide provides an in-depth framework for assessing the foundational significance of theoretical computer science results. It details the rigorous criteria used by top-tier conferences like FOCS (Foundations of Computer Science) to judge a paper's impact, focusing on its consequence, how it overcomes known obstacles, and its durability beyond best constants. It also maps various research types (e.g., cryptographic, algorithmic, learning theory) to the most suitable venue (e.g., FOCS, STOC, SODA, CCC).