13 papers
Teach-to-Reason: Competition-Guided Reasoning with a Self-Improving Teacher
Xiao Han, Hao Liu, Zhimin Bao +5
Chest X-ray visual question answering (CXR VQA) requires models not only to predict correct answers, but also to produce reliable medical reasoning. However, existing reinforcement…
DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation
Taiyi Su, Jian Zhu, Tianjian Wang +9
Real-world household robots require Vision-Language-Action (VLA) foundation models that can acquire reusable manipulation skills across diverse objects, task conditions, and househ…
SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
Kuan Li, Shuo Zhang, Huacan Wang +12
Smart homes are evolving toward complex state-dependent living environments, requiring Large Language Models (LLMs) to reason over user intent, preferences, and multi-device intera…
HomeFlow: A Data Flywheel for Smart Home Agent Training with Verifiable Simulation
Yi Gu, Huacan Wang, Shuo Zhang +10
Large language model agents are moving beyond text-only interaction toward physical-world control, with smart homes as a representative domain. Real domestic interaction requires u…
ECHO: Efficient Chest X-ray Report Generation with One-step Block Diffusion
Lifeng Chen, Tianqi You, Hao Liu +8
Chest X-ray report generation (CXR-RG) has the potential to substantially alleviate radiologists' workload. However, conventional autoregressive vision--language models (VLMs) suff…
SemaClaw: A Step Towards General-Purpose Personal AI Agents through Harness Engineering
Ningyan Zhu, Huacan Wang, Jie Zhou +8
The rise of OpenClaw in early 2026 marks the moment when millions of users began deploying personal AI agents into their daily lives, delegating tasks ranging from travel planning…