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 […]


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

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 […]


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

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 […]


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

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Jing Wang, , , | Summary: Since the advent of autonomous driving technology, it has experienced remarkable progress over the last decade. However, most existing research still struggles to address the challenges posed by environments where multiple vehicles have to interact seamlessly. This study aims […]


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Harnessing Bayesian Statistics to Accelerate Iterative Quantum Amplitude Estimation

Kavli Affiliate: Li Xin Li| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:We establish a unified statistical framework that underscores the crucial role statistical inference plays in Quantum Amplitude Estimation (QAE), a task essential to fields ranging from chemistry to finance and machine learning. We use this framework to harness Bayesian statistics for improved […]


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Growth rates for the Hölder coefficients of the linear stochastic fractional heat equation with rough dependence in space

Kavli Affiliate: Ran Wang | First 5 Authors: Chang Liu, Chang Liu, , , | Summary: We study the linear stochastic fractional heat equation $$ fracpartialpartial tu(t,x)=-(-Delta)^fracalpha2u(t,x)+dotW(t,x), quad t>0, quad xinmathbbR, $$ where $-(-Delta)^fracalpha2$ denotes the fractional Laplacian with power $alphain (1,2)$, and the driving noise $dotW$ is a centered Gaussian field that is white […]


Continue.. Growth rates for the Hölder coefficients of the linear stochastic fractional heat equation with rough dependence in space

Energy Extraction From the Kerr-Bertotti-Robinson Black Hole via Magnetic Reconnection under Circular Plasma and Plunging Plasma

Kavli Affiliate: Ke Wang | First 5 Authors: Xiao-Xiong Zeng, Xiao-Xiong Zeng, , , | Summary: Recently, a class of exact solutions describing rotating black holes immersed in a uniform magnetic field has been proposed, and various properties of such black holes remain unclear. This paper aims to explore how to extract energy based on […]


Continue.. Energy Extraction From the Kerr-Bertotti-Robinson Black Hole via Magnetic Reconnection under Circular Plasma and Plunging Plasma

Energy Extraction From the Kerr-Bertotti-Robinson Black Hole via Magnetic Reconnection under Circular Plasma and Plunging Plasma

Kavli Affiliate: Ke Wang | First 5 Authors: Xiao-Xiong Zeng, Xiao-Xiong Zeng, , , | Summary: Recently, a class of exact solutions describing rotating black holes immersed in a uniform magnetic field has been proposed, and various properties of such black holes remain unclear. This paper aims to explore how to extract energy based on […]


Continue.. Energy Extraction From the Kerr-Bertotti-Robinson Black Hole via Magnetic Reconnection under Circular Plasma and Plunging Plasma

HLSDebugger: Identification and Correction of Logic Bugs in HLS Code with LLM Solutions

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Jing Wang, , , | Summary: High-level synthesis (HLS) accelerates hardware design by enabling the automatic translation of high-level descriptions into efficient hardware implementations. However, debugging HLS code is a challenging and labor-intensive task, especially for novice circuit designers or software engineers without sufficient hardware […]


Continue.. HLSDebugger: Identification and Correction of Logic Bugs in HLS Code with LLM Solutions