Skill UI

This guide provides strict guidelines for authors writing the "Related Work" section for top-tier programming language theory conferences like POPL. It emphasizes moving beyond general literature reviews to pinpoint precise, technical "delta sentences" that prove novelty against neighboring formal systems. It covers citation standards, venue mapping, and attribution verification for maximum academic impact.

A comprehensive guide detailing how to structure a technical paper (such as those submitted to POPL) across three components: the main body, the detailed appendix, and anonymous supplementary artifacts. It covers content placement, ensuring internal consistency between sketches and proofs, and methods for maintaining full double-blind anonymity during submission.

Covers best practices for writing highly technical academic papers, particularly in programming language theory. It guides authors on structuring their work to build a strong 'ramp' from initial concrete programs and informal motivation to rigorous formal proofs and theorems, ensuring clarity and avoiding common pitfalls like unmotivated formalism or ambiguous notation.

A comprehensive guide for researchers detailing how to structure the 'Related Work' section for top-tier parallel computing conferences like PPoPP. It emphasizes 'delta-first' comparison, covering specific technical lanes (concurrent data structures, runtimes, GPU acceleration, memory models), and ensuring proper academic positioning against major parallel systems venues.

A comprehensive deep dive into the PPoPP conference review pipeline. This guide models the single-round, double-blind review process, detailing how submissions are evaluated by the Program Committee and External Review Committee. It covers critical aspects such as the author response rebuttal, automatic poster consideration, and the specific technical axes reviewers prioritize (e.g., scalability, concurrency correctness, baseline honesty) for parallel programming research.

A comprehensive guide detailing the rigorous standards required for submitting parallel programming research to top-tier academic venues. It covers crucial topics such as proving concurrency correctness, demonstrating measurable scalability using speedup curves, adhering to strict formatting (10 pages, two-column layout), and structuring the technical contribution to satisfy expert reviewers.

This guide details the rigorous methodology for conducting systematic literature reviews and meta-science pieces, particularly for integrative reviews in psychology (PoPS style). It instructs researchers on how to systematically gather evidence across multiple sub-areas by utilizing techniques like forward/backward snowballing, comprehensive database sweeps (e.g., PsycINFO), and developing detailed evidence matrices. The focus is on synthesizing findings and establishing replicable search protocols to ensure academic rigor and comprehensiveness, moving beyond simple summarization.

A comprehensive guide for positioning computer science manuscripts for the Privacy Enhancing Technologies Symposium (PETS). It helps authors assess if their research matches the venue's core focus (e.g., differential privacy, anonymity) and provides a detailed framework for structuring empirical evidence against a clear adversary model to maximize acceptance chances.

A comprehensive guide designed for authors targeting PRX Quantum. It helps determine the suitability of manuscripts in quantum information science, quantum computing, or quantum technologies. The skill provides detailed guidance on the journal's scientific scope, required significance bar, structure, and open-access submission standards.

This guide outlines the rigorous methodology for developing theoretical arguments in psychological review papers. Instead of presenting raw data, the focus is on deriving specific, falsifiable predictions from a model's core assumptions. Techniques involve confronting these predictions against existing published evidence and rigorously comparing them head-to-head with rival theoretical models, ensuring logical and quantitative soundness.

A comprehensive guide for strengthening causal identification strategies (DID, IV, RDD, RCT) for high-stakes academic publications. It details modern econometric estimators, required diagnostic checks (pre-trends, density tests, weak-IV robustness), and the philosophical shift from technique to answering a big economic question, essential for submitting to top journals like the Quarterly Journal of Economics (QJE).

This guide provides detailed best practices for presenting empirical results, specifically tailored for top-tier economics journals like the QJE. It emphasizes shifting from 'table-heavy' to 'figure-forward' visualization, covering techniques for event-study plots, RDD discontinuity plots, and ensuring all exhibits are self-contained, readable, and follow strict academic formatting standards.