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Tsinghua Shenzhen International Graduate School, Shenzhen, China, National Supercomputing Center in Shenzhen, Shenzhen, China
Tsinghua AI7
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Late visual-token updates can be safely ignored, leading to a 33.7% reduction in computational load without sacrificing performance.
Achieving over 555 FPS in tactile simulations, TaCauchy delivers unprecedented accuracy in mechanical stress computation for robotics applications.
Today's best multimodal LLMs are surprisingly inept at using tools to solve agricultural tasks, struggling with everything from planning to error recovery.
VLMs forget visual reasoning skills in continual learning because today's methods over-protect the language model while neglecting the vision encoder.
Extracting agricultural parcels from satellite imagery gets a whole lot harder (and more realistic) with a new dataset focused on the complex, irregular, and heterogeneous terrain of terraced farms.
Achieve state-of-the-art performance in multimodal remote sensing semantic segmentation with significantly fewer trainable parameters by using a novel parameter-efficient and modality-balanced symmetric fusion framework.
Injecting physics-based priors derived from MLLMs at decoding time significantly boosts weather forecasting accuracy and stability, even in long autoregressive rollouts.
