This AI Paper Propose the UI-R1 Framework that Extends Rule-based Reinforcement Learning to GUI Action Prediction Tasks

This AI Paper Propose the UI-R1 Framework that Extends Rule-based Reinforcement Learning to GUI Action Prediction Tasks

Supervised fine-tuning (SFT) is the standard training paradigm for large language models (LLMs) and graphic user interface (GUI) agents. However, SFT demands high-quality labeled datasets, resulting in extended training periods and high computational expenses. This dependence on extensive data creates bottlenecks in AI development workflows. Moreover, existing VLM-based GUI agents trained through SFT show performance deficiencies when confronted…