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ShiZhi: A Chinese Lightweight Large Language Model for Court View Generation
Zhitian Hou, Kun Zeng
https://arxiv.org/abs/2510.09297 https://arxiv.org/pdf/2…

ShiZhi: A Chinese Lightweight Large Language Model for Court View Generation
Criminal Court View Generation (CVG) is a fundamental task in legal artificial intelligence, aiming to automatically generate the "Court View" section of a legal case document. Generating court views is challenging due to the diversity and complexity of case facts, and directly generating from raw facts may limit performance. In this paper, we present ShiZhi, the first large language model (LLM) specifically designed for court view generation. We construct a Chinese Court View Generation datase…

Generative Diffusion Contrastive Network for Multi-View Clustering
Jian Zhu, Xin Zou, Xi Wang, Ning Zhang, Bian Wu, Yao Yang, Ying Zhou, Lingfang Zeng, Chang Tang, Cheng Luo
https://arxiv.org/abs/2509.09527

Generative Diffusion Contrastive Network for Multi-View Clustering
In recent years, Multi-View Clustering (MVC) has been significantly advanced under the influence of deep learning. By integrating heterogeneous data from multiple views, MVC enhances clustering analysis, making multi-view fusion critical to clustering performance. However, there is a problem of low-quality data in multi-view fusion. This problem primarily arises from two reasons: 1) Certain views are contaminated by noisy data. 2) Some views suffer from missing data. This paper proposes a novel…

Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey
Yan Gong, Naibang Wang, Jianli Lu, Xinyu Zhang, Yongsheng Gao, Jie Zhao, Zifan Huang, Haozhi Bai, Nanxin Zeng, Nayu Su, Lei Yang, Ziying Song, Xiaoxi Hu, Xinmin Jiang, Xiaojuan Zhang, Susanto Rahardja
https://arxiv.org/abs/2508.07560…

Progressive Bird's Eye View Perception for Safety-Critical Autonomous Driving: A Comprehensive Survey
Bird's-Eye-View (BEV) perception has become a foundational paradigm in autonomous driving, enabling unified spatial representations that support robust multi-sensor fusion and multi-agent collaboration. As autonomous vehicles transition from controlled environments to real-world deployment, ensuring the safety and reliability of BEV perception in complex scenarios - such as occlusions, adverse weather, and dynamic traffic - remains a critical challenge. This survey provides the first comprehens…

Gravitational wave echos from physical black holes
Yu-Song Cao, YanXia Liu, Ding-Fang Zeng
https://arxiv.org/abs/2510.11518 https://arxiv.org/pdf/2510.1151…

Gravitational wave echos from physical black holes
Gravitational wave echos from the coalescence of black hole binaries are often viewed as signals beyond general relativity or standard model. In this work, we show that these echos are inevitable in the black holes coalescence described by standard general relativity. This is because it is the physical black holes formed through gravitational collapse serve as the true description of astronomical black holes. For physical black holes, only their asymptotic structure before the horizon forms are…

Fine-grained Video Dubbing Duration Alignment with Segment Supervised Preference Optimization
Chaoqun Cui, Liangbin Huang, Shijing Wang, Zhe Tong, Zhaolong Huang, Xiao Zeng, Xiaofeng Liu
https://arxiv.org/abs/2508.08550

Fine-grained Video Dubbing Duration Alignment with Segment Supervised Preference Optimization
Video dubbing aims to translate original speech in visual media programs from the source language to the target language, relying on neural machine translation and text-to-speech technologies. Due to varying information densities across languages, target speech often mismatches the source speech duration, causing audio-video synchronization issues that significantly impact viewer experience. In this study, we approach duration alignment in LLM-based video dubbing machine translation as a prefer…

Newton series representation of completely monotone functions
Thomas Lamby, Jean-Luc Marichal, Na\"im Zena\"idi
https://arxiv.org/abs/2510.11577 https://

Newton series representation of completely monotone functions
We prove that every completely monotone function defined on a right-unbounded open interval admits a Newton series expansion at every point of that interval. This result can be viewed as an analog of Bernstein's little theorem for absolutely monotone functions. As an application, we use it to study principal indefinite sums, which are constructed via a broad generalization of Bohr-Mollerup's theorem.

C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
Zeng Tao, Zheng Ding, Zeyuan Chen, Xiang Zhang, Leizhi Li, Zhuowen Tu
https://arxiv.org/abs/2510.04539 ht…

C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing
Existing 2D-lifting-based 3D editing methods often encounter challenges related to inconsistency, stemming from the lack of view-consistent 2D editing models and the difficulty of ensuring consistent editing across multiple views. To address these issues, we propose C3Editor, a controllable and consistent 2D-lifting-based 3D editing framework. Given an original 3D representation and a text-based editing prompt, our method selectively establishes a view-consistent 2D editing model to achieve sup…

TalkCuts: A Large-Scale Dataset for Multi-Shot Human Speech Video Generation
Jiaben Chen, Zixin Wang, Ailing Zeng, Yang Fu, Xueyang Yu, Siyuan Cen, Julian Tanke, Yihang Chen, Koichi Saito, Yuki Mitsufuji, Chuang Gan
https://arxiv.org/abs/2510.07249

TalkCuts: A Large-Scale Dataset for Multi-Shot Human Speech Video Generation
In this work, we present TalkCuts, a large-scale dataset designed to facilitate the study of multi-shot human speech video generation. Unlike existing datasets that focus on single-shot, static viewpoints, TalkCuts offers 164k clips totaling over 500 hours of high-quality human speech videos with diverse camera shots, including close-up, half-body, and full-body views. The dataset includes detailed textual descriptions, 2D keypoints and 3D SMPL-X motion annotations, covering over 10k identities…

Zenbo Patrol: A Social Assistive Robot Based on Multimodal Deep Learning for Real-time Illegal Parking Recognition and Notification
Jian-jie Zheng, Chih-kai Yang, Po-han Chen, Lyn Chao-ling Chen
https://arxiv.org/abs/2510.04190

Zenbo Patrol: A Social Assistive Robot Based on Multimodal Deep Learning for Real-time Illegal Parking Recognition and Notification
In the study, the social robot act as a patrol to recognize and notify illegal parking in real-time. Dual-model pipeline method and large multimodal model were compared, and the GPT-4o multimodal model was adopted in license plate recognition without preprocessing. For moving smoothly on a flat ground, the robot navigated in a simulated parking lot in the experiments. The robot changes angle view of the camera automatically to capture the images around with the format of license plate number. F…

Probing Horndeski Gravity via Kerr Black Hole: Insights from Thin Accretion Disks and Shadows with EHT Observations
Xiao-Xiong Zeng, Chen-Yu Yang, M. Israr Aslam, Rabia Saleem
https://arxiv.org/abs/2509.05803

Probing Horndeski Gravity via Kerr Black Hole: Insights from Thin Accretion Disks and Shadows with EHT Observations
In this study, we have considered the Kerr-like black hole (BH) model in Horndeski gravity and analyse the visual characteristics of shadow images under two illumination models, such as a celestial light source and a thin accretion disk. To capture the BH shadow images, we utilise a recent fisheye camera model and ray-tracing procedures. In this view, we carefully addressed the influence of the spin parameter $a$ and the hair parameter $h$ on the BH shadow images. The results indicate that for …