Tag
RubSE is a framework that uses rubric-guided self-evolution to enhance the stability of UI-to-code generation by mitigating visual repair coupling and trajectory collapse.
CRAFT is a new LLM framework for iterative refinement of temporal reasoning over clinical narratives, introducing a verifier-based feedback mechanism and the MedTempo benchmark for vaccine adverse-event reports.
This paper proposes an iterative moderation framework that refines and reuses annotation guidelines to improve LLM-based annotation performance, validated on biomedical NER tasks with GPT, Gemini, and DeepSeek models.
This paper introduces TokenDrift, a drifting objective that refines discrete diffusion language models by lifting categorical predictions to a continuous semantic space for anti-symmetric drifting, significantly improving generation quality under a fixed number of denoising steps.
A blog post explaining how to use refinement mappings to preserve external properties during database schema changes, using examples of migrating a boolean column to a nullable timestamp and then to event sourcing.