12 papers
DriftingVLA: Native One-Step Vision-Language-Action Generation via Per-Dimension Temporal Drifting
Yuxuan Gao, Shiqi Zhang, Yedong Shen +6
Conventional flow-based vision-language-action (VLA) models support expressive continuous action generation but rely on multi-step refinement to produce each action chunk, increasi…
ReTouch: Empowering Contact-Rich Dexterous Manipulation with Online-Refined Tactile Prediction
Shiqi Zhang, Xin Zhang, Yedong Shen +9
Fusing tactile signals has proven effective for contact-rich manipulation, enabling robots to perceive contact states and adapt to rapidly changing physical interactions. Yet effec…
Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation
Shenghui Zhang, YuXuan Gao, Songwei Zhao +3
With the rapid development of autonomous aerial systems, Unmanned Aerial Vehicles (UAVs) are increasingly deployed in applications such as inspection, environmental monitoring, and…
GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation
Yuan Zhang, Shiqi Zhang, Yedong Shen +11
Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot emb…
Distribution-Free Uncertainty Quantification for Continuous AI Agent Evaluation
Yuxuan Gao, Megan Wang, Yi Ling Yu
We adapt split conformal prediction and adaptive conformal inference (ACI) to continuous AI agent evaluation, providing distribution-free coverage guarantees for forecasted quality…
DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows
Yuxuan Gao, Megan Wang, Yi Ling Yu +2
We introduce DecisionBench, a benchmark substrate for emergent delegation in long-horizon agentic workflows. The substrate fixes a task suite (GAIA, tau-bench, BFCL multi-turn), a…
Token Arena: A Continuous Benchmark Unifying Energy and Cognition in AI Inference
Yuxuan Gao, Megan Wang, Yi Ling Yu
Public inference benchmarks compare AI systems at the model and provider level, but the unit at which deployment decisions are actually made is the endpoint: the (provider, model,…
AgentPulse: A Continuous Multi-Signal Framework for Evaluating AI Agents in Deployment
Yuxuan Gao, Megan Wang, Yi Ling Yu
Static benchmarks measure what AI agents can do at a fixed point in time but not how they are adopted, maintained, or experienced in deployment. We introduce AgentPulse, a continuo…
Omnimodal Dataset Distillation via High-order Proxy Alignment
Yuxuan Gao, Xiaohao Liu, Xiaobo Xia +1
Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving training performance, but existing methods are largely restricted to single-modal…
Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control
Yuxuan Gao, Yedong Shen, Shiqi Zhang +6
Diffusion policies effectively model multimodal action distributions for robotic manipulation, but their iterative denoising requires tens to hundreds of network function evaluatio…
HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection
Han Zhou, Yuxuan Gao, Yinchao Du +1
Unsupervised industrial anomaly detection (UAD) is essential for modern manufacturing inspection, where defect samples are scarce and reliable detection is required. In this paper,…
SafeWork-R1: Coevolving Safety and Intelligence under the AI-45 Law
Shanghai AI Lab, :, Yicheng Bao +115
We introduce SafeWork-R1, a cutting-edge multimodal reasoning model that demonstrates the coevolution of capabilities and safety. It is developed by our proposed SafeLadder framewo…