Tag
This paper presents a method using LLMs for stance detection in scientific discourse, specifically identifying realism vs. instrumentalism in Bayesian cognitive science articles. The approach combines theory-driven coding, expert annotations, and prompt optimization to achieve high reliability.
A developer reports that using Qwen3.6-27B for vibe coding introduced subtle bugs in their codebase and asks the community for best practices to reduce errors when working with the model.