4 papers
Why Code, Why Now: An Information-Theoretic Perspective on the Limits of Machine Learning
Zhimin Zhao
This paper offers a new perspective on the limits of machine learning: the ceiling on progress is set not by model size or algorithm choice but by the information structure of the…
Gradual Cognitive Externalization: From Modeling Cognition to Constituting It
Zhimin Zhao
Developers are publishing AI agent skills that replicate a colleague's communication style, encode a supervisor's mentoring heuristics, or preserve a person's behavioral repertoire…
SWE-Arena: An Interactive Platform for Evaluating Foundation Models in Software Engineering
Zhimin Zhao
Foundation models (FMs), particularly large language models (LLMs), have shown significant promise in various software engineering (SE) tasks, including code generation, debugging,…
On the Workflows and Smells of Leaderboard Operations (LBOps): An Exploratory Study of Foundation Model Leaderboards
Zhimin Zhao, Abdul Ali Bangash, Filipe Roseiro Côgo +2
Foundation models (FM), such as large language models (LLMs), which are large-scale machine learning (ML) models, have demonstrated remarkable adaptability in various downstream so…