Skill UI

This skill provides a comprehensive guide for manuscript authors targeting the StarSem Conference on Computational Semantics (*SEM). It helps authors determine the conference fit, refine framing, establish the necessary evidence bar, and strategize submissions for topics related to meaning representation, semantic parsing, and inference. It is a specialized venue-selection and re-framing tool for advanced NLP/CS papers.

This comprehensive tool assesses the suitability of a manuscript for the Strategic Management Journal (SMJ). It guides authors through critical self-checks, focusing on the necessity of a clear contribution to strategy theory, the required level of empirical rigor (e.g., handling endogeneity), and ensuring the core focus remains on firm-level strategic decisions and performance outcomes. Essential for pre-submission refinement.

This guide outlines the rigorous process for submitting and evaluating research artifacts for academic conferences (TACAS/ETAPS). It details the mandatory two-round evaluation system, covering tool-demonstration papers and general research case studies. Authors must package their work to achieve badges like Available, Functional, and Reusable, ensuring maximum reproducibility and environmental compatibility on a clean virtual machine.

This comprehensive guide outlines best practices for designing and auditing empirical evaluations of formal verification tools and algorithms. It stresses the use of shared, community-accepted benchmarks, ensuring fair comparison against the strongest baselines with equal resources, meticulous reporting of all metrics, validating results for soundness, and guaranteeing full reproducibility on clean virtual environments.

This guide provides detailed guidelines for authors submitting to top-tier formal methods conferences (like TACAS). It emphasizes moving beyond simple literature summaries by employing a "delta-first" approach. Authors must precisely position their algorithm or tool by contrasting its novel features, guarantees, or scaling benefits against the nearest prior work, while also crediting underlying infrastructure and covering major verification venues.

A comprehensive guide detailing the complex submission and evaluation pipeline for TACAS (Tools and Algorithms for Scientific Applications). It models key features such as category-specific blind review, the mandatory parallel artifact evaluation for tool papers, and the single-round conference decision-making process, helping authors strategically prepare their submissions.

A comprehensive pre-submission checklist for authors preparing papers for TACAS/ETAPS. It guides users through selecting the correct paper category (research, tool, case-study), adhering to specific Springer LNCS page limits, managing double-blind vs. single-blind review rules, and correctly staging mandatory tool artifacts to ensure acceptance readiness.

This guide assists researchers in determining the optimal venue for their formal verification project. It helps decide whether the work belongs at TACAS (ETAPS) or a sibling conference (like CAV or VMCAI), depending on the emphasis (tool vs. theory), and guides the selection among the four distinct contribution categories (Research, Tool, Case-study, Demonstration).

This comprehensive guide provides a backward-planning workflow for submissions to the TACAS conference. It meticulously details the entire academic publishing lifecycle, from initial category selection and evidence locking to mandatory tool artifact submission, rebuttal, and camera-ready preparation. It is tailored for understanding the unique single annual review cycle and parallel tool/paper review structure.

This guide provides comprehensive rules for authors submitting research papers to verification experts (TACAS/LNCS). It emphasizes stating the core contribution immediately, explicitly claiming soundness or completeness, supporting empirical claims with fair and reproducible benchmarks, and aligning the paper structure with its specific category (research, tool, case study).

A comprehensive methodological guide for designing rigorous academic studies in accounting. It details advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and experimental setups—to establish credible causal identification. Use this guide when your research challenge is solving endogeneity or isolating a specific economic channel from complex, non-random variables.

This skill guides authors on positioning information retrieval (IR) work for the Text REtrieval Conference (TREC). It functions as a venue-selection and manuscript re-framing tool, ensuring the submission aligns with TREC's focus on shared evaluation tracks, test collections, and NIST-style benchmarking. It helps authors structure evidence, understand reviewer expectations, and distinguish the work from general CS conference submissions.