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On The Road - To Xi’An/ Beings 👁️‍🗨️
在路上 - 去西安/ 灵 👁️‍🗨️
📷 Pentax MX
🎞️Kodak Double-X 5222
#filmphotography #Photography #blackandwhite

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Our Suquamish subject was safely located and extracted! …

Let's Grow an Unbiased Community: Guiding the Fairness of Graphs via New Links
Jiahua Lu, Huaxiao Liu, Shuotong Bai, Junjie Xu, Renqiang Luo, Enyan Dai
https://arxiv.org/abs/2508.15499

Let's Grow an Unbiased Community: Guiding the Fairness of Graphs via New Links
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications. However, due to the biases in the graph structures, graph neural networks face significant challenges in fairness. Although the original user graph structure is generally biased, it is promising to guide these existing structures toward unbiased ones by introducing new links. The fairness guidance via new links could foster unbiased communities, thereby enhancing fairness in downstream applications. To ad…

The practical issues of side-channel-secure quantum key distribution
Cong Jiang, Xiao-Long Hu, Zong-Wen Yu, Hai Xu, Xiang-Bin Wang
https://arxiv.org/abs/2508.15197 https://

The practical issues of side-channel-secure quantum key distribution
Quantum Key Distribution (QKD) leverages the principles of quantum mechanics to provide theoretically unconditional security for cryptographic key sharing. However, practical implementations remain vulnerable due to non-ideal devices and potential security loopholes at both the source and detection sides of QKD systems. The side-channel-secure (SCS) protocol addresses these challenges by encoding bits in vacuum and non-vacuum states and introducing a third-party measurement node, thereby repell…

A first look at License Variants in the PyPI Ecosystem
Weiwei Xu, Hengzhi Ye, Kai Gao, Minghui Zhou
https://arxiv.org/abs/2507.14594 https://

A first look at License Variants in the PyPI Ecosystem
Open-source licenses establish the legal foundation for software reuse, yet license variants, including both modified standard licenses and custom-created alternatives, introduce significant compliance complexities. Despite their prevalence and potential impact, these variants are poorly understood in modern software systems, and existing tools do not account for their existence, leading to significant challenges in both effectiveness and efficiency of license analysis. To fill this knowledge g…

MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging
Jinwei Tang (Katie), Jiayin Qin (Katie), Nuo Xu (Katie), Pragnya Sudershan Nalla (Katie), Yu Cao (Katie), Yang (Katie), Zhao, Caiwen Ding
https://arxiv.org/abs/2508.14053

MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging
As program workloads (e.g., AI) increase in size and algorithmic complexity, the primary challenge lies in their high dimensionality, encompassing computing cores, array sizes, and memory hierarchies. To overcome these obstacles, innovative approaches are required. Agile chip design has already benefited from machine learning integration at various stages, including logic synthesis, placement, and routing. With Large Language Models (LLMs) recently demonstrating impressive proficiency in Hardwa…

Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
Guoliang He, Youhe Jiang, Wencong Xiao, Kaihua Jiang, Shuguang Wang, Jun Wang, Zixian Du, Zhuo Jiang, Xinlei Zhang, Binhang Yuan, Eiko Yoneki
https://arxiv.org/abs/2509.15940

Efficient Pre-Training of LLMs via Topology-Aware Communication Alignment on More Than 9600 GPUs
The scaling law for large language models (LLMs) depicts that the path towards machine intelligence necessitates training at large scale. Thus, companies continuously build large-scale GPU clusters, and launch training jobs that span over thousands of computing nodes. However, LLM pre-training presents unique challenges due to its complex communication patterns, where GPUs exchange data in sparse yet high-volume bursts within specific groups. Inefficient resource scheduling exacerbates bandwidt…

AudioSet-R: A Refined AudioSet with Multi-Stage LLM Label Reannotation
Yulin Sun, Qisheng Xu, Yi Su, Qian Zhu, Yong Dou, Xinwang Liu, Kele Xu
https://arxiv.org/abs/2508.15429 ht…

AudioSet-R: A Refined AudioSet with Multi-Stage LLM Label Reannotation
AudioSet is a widely used benchmark in the audio research community and has significantly advanced various audio-related tasks. However, persistent issues with label accuracy and completeness remain critical bottlenecks that limit performance in downstream applications.To address the aforementioned challenges, we propose a three-stage reannotation framework that harnesses general-purpose audio-language foundation models to systematically improve the label quality of AudioSet. The framework empl…

DualNILM: Energy Injection Identification Enabled Disaggregation with Deep Multi-Task Learning
Xudong Wang, Guoming Tang, Junyu Xue, Srinivasan Keshav, Tongxin Li, Chris Ding
https://arxiv.org/abs/2508.14600

DualNILM: Energy Injection Identification Enabled Disaggregation with Deep Multi-Task Learning
Non-Intrusive Load Monitoring (NILM) offers a cost-effective method to obtain fine-grained appliance-level energy consumption in smart homes and building applications. However, the increasing adoption of behind-the-meter energy sources, such as solar panels and battery storage, poses new challenges for conventional NILM methods that rely solely on at-the-meter data. The injected energy from the behind-the-meter sources can obscure the power signatures of individual appliances, leading to a sign…

On The Road - To Xi’An/ Geometry 📐
在路上 - 去西安/ 几何 📐
📷 Pentax MX
🎞️Fujifilm Neopan F, expired 1993
#filmphotography #Photography #blackandwhite