Argues for rigorous scientific studies on the impact and risks of using LLMs in software development, highlighting current lack of impartial research.
Explores the history of data science through early 20th-century rat diet experiments, drawing parallels to modern statistical methods.
Analyzes three experiments on the ICML 2020 peer-review process, focusing on resubmission bias, discussion effects, and reviewer recruiting.
Discusses the proposal to lower p-value thresholds in statistical analysis, arguing it addresses symptoms not root causes of unreliable research.
A guide to critically reading academic papers in computer science, emphasizing active engagement and contextual understanding.
Explores the importance of reproducible science in computer science, focusing on reproducibility, replicability, and reusability of software and data.
The article debunks common misinterpretations of the Dunning-Kruger effect by analyzing the original study's data and findings.
Explains the meaning of ACL 2014 peer review scores and criteria for natural language processing papers.
A critique of common pitfalls and unproductive patterns in statistics research presentations, aimed at improving academic discourse.
