2 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
Rubric-as-Experts: Case-Specific MQM Rubrics for Translation Quality Evaluation
Weilu Xu, Yunzhi Shen, Xinye Wang +2
Large language models (LLMs) have shown strong potential in fine-grained translation quality evaluation (QE), yet existing MQM-based approaches typically rely on fixed rubric confi…
PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning
Yunzhi Shen, Hao Zhou, Xin Huang +3
Reinforcement learning (RL) has shown strong promise for LLM-based machine translation, with recent methods such as GRPO demonstrating notable gains; nevertheless, translation-orie…
ScreenLLM: Stateful Screen Schema for Efficient Action Understanding and Prediction
Yiqiao Jin, Stefano Petrangeli, Yu Shen +1
Graphical User Interface (GUI) agents are autonomous systems that interpret and generate actions, enabling intelligent user assistance and automation. Effective training of these a…
GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration
Yue Fan, Handong Zhao, Ruiyi Zhang +3
Graphical User Interface (GUI) action grounding is a critical step in GUI automation that maps language instructions to actionable elements on GUI screens. Most recent works of GUI…