Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusion

Kavli Affiliate: Jing Wang | First 5 Authors: Wentao Qu, Wentao Qu, , , | Summary: Denoising Diffusion Probabilistic Models (DDPMs) have shown success in robust 3D object detection tasks. Existing methods often rely on the score matching from 3D boxes or pre-trained diffusion priors. However, they typically require multi-step iterations in inference, which limits […]


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DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

Kavli Affiliate: Zhuo Li | First 5 Authors: Haonan Yang, Haonan Yang, , , | Summary: Time Series Forecasting (TSF) faces persistent challenges in modeling intricate temporal dependencies across different scales. Despite recent advances leveraging different decomposition operations and novel architectures based on CNN, MLP or Transformer, existing methods still struggle with static decomposition strategies, […]


Continue.. DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

Kavli Affiliate: Zhuo Li | First 5 Authors: Haonan Yang, Haonan Yang, , , | Summary: Time Series Forecasting (TSF) faces persistent challenges in modeling intricate temporal dependencies across different scales. Despite recent advances leveraging different decomposition operations and novel architectures based on CNN, MLP or Transformer, existing methods still struggle with static decomposition strategies, […]


Continue.. DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting

Theoretical Diagnostics for the Physical Conditions in Active Galactic Nuclei under the View of JWST

Kavli Affiliate: Claudio Ricci | First 5 Authors: Lulu Zhang, Lulu Zhang, , , | Summary: With excellent spectral and angular resolutions and, especially, sensitivity, the JWST allows us to observe infrared emission lines that were previously inaccessible or barely accessible. These emission lines are promising for evaluating the physical conditions in different galaxies. Based […]


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Revisiting the Proper Motions of M31 and M33 Using Massive Supergiant Stars with Gaia DR3

Kavli Affiliate: Huawei Zhang | First 5 Authors: Hao Wu, Hao Wu, , , | Summary: The proper motions (PMs) of M31 and M33 are key to understanding the Local Group’s dynamical evolution. However, measurement discrepancies between Gaia blue and red samples, regarding whether the transverse velocity is remarkable, introduce significant ambiguity. In this work, […]


Continue.. Revisiting the Proper Motions of M31 and M33 Using Massive Supergiant Stars with Gaia DR3

Revisiting the Proper Motions of M31 and M33 Using Massive Supergiant Stars with Gaia DR3

Kavli Affiliate: Huawei Zhang | First 5 Authors: Hao Wu, Hao Wu, , , | Summary: The proper motions (PMs) of M31 and M33 are key to understanding the Local Group’s dynamical evolution. However, measurement discrepancies between Gaia blue and red samples, regarding whether the transverse velocity is remarkable, introduce significant ambiguity. In this work, […]


Continue.. Revisiting the Proper Motions of M31 and M33 Using Massive Supergiant Stars with Gaia DR3

Discovery of a Little Red Dot candidate at $zgtrsim10$ in COSMOS-Web based on MIRI-NIRCam selection

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: Takumi S. Tanaka, Takumi S. Tanaka, , , | Summary: JWST has revealed a new high-redshift population called little red dots (LRDs). Since LRDs may be in the early phase of black hole growth, identifying them in the early universe is crucial for understanding the formation of […]


Continue.. Discovery of a Little Red Dot candidate at $zgtrsim10$ in COSMOS-Web based on MIRI-NIRCam selection

DivControl: Knowledge Diversion for Controllable Image Generation

Kavli Affiliate: Jing Wang | First 5 Authors: Yucheng Xie, Yucheng Xie, , , | Summary: Diffusion models have advanced from text-to-image (T2I) to image-to-image (I2I) generation by incorporating structured inputs such as depth maps, enabling fine-grained spatial control. However, existing methods either train separate models for each condition or rely on unified architectures with […]


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LLM4Rail: An LLM-Augmented Railway Service Consulting Platform

Kavli Affiliate: Zhuo Li | First 5 Authors: Zhuo Li, Zhuo Li, , , | Summary: Large language models (LLMs) have significantly reshaped different walks of business. To meet the increasing demands for individualized railway service, we develop LLM4Rail – a novel LLM-augmented railway service consulting platform. Empowered by LLM, LLM4Rail can provide custom modules […]


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FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning

Kavli Affiliate: Zhuo Li | First 5 Authors: Jiajun Cao, Jiajun Cao, , , | Summary: Vision-Language-Action (VLA) models have demonstrated significant potential in complex scene understanding and action reasoning, leading to their increasing adoption in end-to-end autonomous driving systems. However, the long visual tokens of VLA models greatly increase computational costs. Current visual token […]


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