Ensuring the long-term integrity and health of bridge structures under diverse structural, environmental, and operational conditions remains a persistent challenge within the structural health monitoring (SHM) community. Although machine learning–aided unsupervised anomaly detect…
Dam displacement monitoring is imperative to assess the operational status and structural safety of dams under various environmental conditions and operational loads. Although most of the dam structures are instrumented with robust in-situ sensing systems, long-term field monitor…
Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel drafters efficiently propose long token sequences in a single forward pass, they suffer from rapid acceptance decay due to a lack o…
Recent advances in video diffusion models have greatly improved visual fidelity, yet their generated motions often violate physical plausibility. We observe a common kinematic failure, "motion entanglement", the unintended coupling of independent motion sources, such as camera mo…
We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual quality and instruction-following capability of the Qwen-Image-2.0 diffusion model. To provide reliabl…