10 papers
Learning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards
Yingyu Shan, Yuhang Guo, Zihao Cheng +7
Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative methods such as GRPO assign uniform c…
PEC-Home: Interpretation of Progressively Elliptical Commands in Smart Homes
Yingyu Shan, Zeming Liu, Silin Li +4
Recent advancements in Large Language Models (LLMs) have empowered home assistants with natural language interaction capabilities. However, current assistants overlook the progress…
Benchmarking Living-Screen-Native GUI Agents on Short-Video Platforms
Jiashu Yao, Heyan Huang, Daiqing Wu +5
GUI agents today assume a static screen, where the world is frozen between two actions. However, real interfaces such as short-video applications violate this assumption, as their…
Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization
Jiashu Yao, Heyan Huang, Daiqing Wu +2
To encourage diverse exploration in reinforcement learning (RL) for large language models (LLMs) without compromising accuracy, we propose Policy Split, a novel paradigm that bifur…
Terminal-World: Scaling Terminal-Agent Environments via Agent Skills
Zihao Cheng, Hongru Wang, Zeming Liu +6
Terminal agents extend Large Language Models with the ability to execute tasks directly in command-line environments, but their progress is bottlenecked by the scarcity of high-qua…
DocOS: Towards Proactive Document-Guided Actions in GUI Agents
Jingjing Liu, Ziye Huang, Zihao Cheng +6
While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric knowledge from pre-training…