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Gaussian Variation Field Diffusion for High-fidelity Video-to-4D Synthesis
Bowen Zhang, Sicheng Xu, Chuxin Wang, Jiaolong Yang, Feng Zhao, Dong Chen, Baining Guo
https://arxiv.org/abs/2507.23785

Gaussian Variation Field Diffusion for High-fidelity Video-to-4D Synthesis
In this paper, we present a novel framework for video-to-4D generation that creates high-quality dynamic 3D content from single video inputs. Direct 4D diffusion modeling is extremely challenging due to costly data construction and the high-dimensional nature of jointly representing 3D shape, appearance, and motion. We address these challenges by introducing a Direct 4DMesh-to-GS Variation Field VAE that directly encodes canonical Gaussian Splats (GS) and their temporal variations from 3D anima…

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
- Differentially Private Distributed Nonconvex Stochastic Optimization with Quantized Communication
Jialong Chen, Jimin Wang, Ji-Feng Zhang

MNV-17: A High-Quality Performative Mandarin Dataset for Nonverbal Vocalization Recognition in Speech
Jialong Mai, Jinxin Ji, Xiaofen Xing, Chen Yang, Weidong Chen, Jingyuan Xing, Xiangmin Xu
https://arxiv.org/abs/2509.18196

MNV-17: A High-Quality Performative Mandarin Dataset for Nonverbal Vocalization Recognition in Speech
Mainstream Automatic Speech Recognition (ASR) systems excel at transcribing lexical content, but largely fail to recognize nonverbal vocalizations (NVs) embedded in speech, such as sighs, laughs, and coughs. This capability is important for a comprehensive understanding of human communication, as NVs convey crucial emotional and intentional cues. Progress in NV-aware ASR has been hindered by the lack of high-quality, well-annotated datasets. To address this gap, we introduce MNV-17, a 7.55-hour…

Symbol Detection in Inter-Symbol Interference Channels using Expectation Propagation with Channel Shortening
Jannis Clausius, Luca Schmid, Laurent Schmalen, Stephan ten Brink
https://arxiv.org/abs/2509.17735

Symbol Detection in Inter-Symbol Interference Channels using Expectation Propagation with Channel Shortening
Iterative message passing detection based on expectation propagation(EP) has demonstrated near-optimum performance in many signal processing and communication scenarios. The method remains feasible even for channel impulse responses (CIRs), where the optimal Bahl-Cocke-Jelinek-Raviv (BCJR) detector is infeasible. However, significant performance degradation occurs for channels with strong inter-symbol interference (ISI), where the initial linear minimum mean square error (LMMSE) estimate is ina…

Safeguarding ISAC Performance in Low-Altitude Wireless Networks Under Channel Access Attack
Jiacheng Wang, Jialing He, Geng Sun, Zehui Xiong, Dusit Niyato, Shiwen Mao, Dong In Kim, Tao Xiang
https://arxiv.org/abs/2508.15838

Safeguarding ISAC Performance in Low-Altitude Wireless Networks Under Channel Access Attack
The increasing saturation of terrestrial resources has driven the exploration of low-altitude applications such as air taxis. Low altitude wireless networks (LAWNs) serve as the foundation for these applications, and integrated sensing and communication (ISAC) constitutes one of the core technologies within LAWNs. However, the openness nature of low-altitude airspace makes LAWNs vulnerable to malicious channel access attacks, which degrade the ISAC performance. Therefore, this paper develops a …

Elk: Exploring the Efficiency of Inter-core Connected AI Chips with Deep Learning Compiler Techniques
Yiqi Liu, Yuqi Xue, Noelle Crawford, Jilong Xue, Jian Huang
https://arxiv.org/abs/2507.11506

Elk: Exploring the Efficiency of Inter-core Connected AI Chips with Deep Learning Compiler Techniques
To meet the increasing demand of deep learning (DL) models, AI chips are employing both off-chip memory (e.g., HBM) and high-bandwidth low-latency interconnect for direct inter-core data exchange. However, it is not easy to explore the efficiency of these inter-core connected AI (ICCA) chips, due to a fundamental tussle among compute (per-core execution), communication (inter-core data exchange), and I/O (off-chip data access). In this paper, we develop Elk, a DL compiler framework to maximiz…

Indoor Fluid Antenna Systems Enabled by Layout-Specific Modeling and Group Relative Policy Optimization
Tong Zhang, Qianren Li, Shuai Wang, Wanli Ni, Jiliang Zhang, Rui Wang, Kai-Kit Wong, Chan-Byoung Chae
https://arxiv.org/abs/2509.15006

Indoor Fluid Antenna Systems Enabled by Layout-Specific Modeling and Group Relative Policy Optimization
The fluid antenna system (FAS) revolutionizes wireless communications by employing position-flexible antennas that dynamically optimize channel conditions and mitigate multipath fading. This innovation is particularly valuable in indoor environments, where signal propagation is severely degraded due to structural obstructions and complex multipath reflections. In this paper, we study the channel modeling and joint optimization of antenna positioning, beamforming, and power allocation for indoor…