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AI & Data Science Preprint PDF DOI

HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation

Xin Zhou, Dingkang Liang, Xiwu Chen, Feiyang Tan, Dingyuan Zhang, Hengshuang Zhao, Xiang Bai ยท 2026

Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominantly focus on future scene generation, often overlโ€ฆ

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AI & Data Science Preprint PDF DOI

RHyVE: Competence-Aware Verification and Phase-Aware Deployment for LLM-Generated Reward Hypotheses

Feiyu Wu, Xu Zheng, Zhuocheng Wang, Yi ming Dai, Hui Li ยท 2026

Large language models (LLMs) make reward design in reinforcement learning substantially more scalable, but generated rewards are not automatically reliable training objectives. Existing work has focusโ€ฆ

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AI & Data Science Preprint PDF DOI

GUI Agents with Reinforcement Learning: Toward Digital Inhabitants

Junan Hu, Jian Liu, Jingxiang Lai, Jiarui Hu, Yiwei Sheng, Shuang Chen, Jian Li, Dazhao Du, Song Guo ยท 2026

Graphical User Interface (GUI) agents have emerged as a promising paradigm for intelligent systems that perceive and interact with graphical interfaces visually. Yet supervised fine-tuning alone cannoโ€ฆ

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AI & Data Science Preprint PDF DOI

Calibrating Attribution Proxies for Reward Allocation in Participatory Weather Sensing

Mark C. Ballandies, Michael T. C. Chiu, Claudio J. Tessone ยท 2026

Large-scale IoT weather sensing networks require incentive mechanisms to sustain participation, yet determining how much value individual data contributions bring to the network remains an open probleโ€ฆ

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Physics Preprint PDF DOI

Discrete Lattice Models for Interface Growth on a Complete Graph

J. M. Marcos, J. J. Melendez, R. Cuerno, J. J. Ruiz-Lorenzo ยท 2026

We investigate the behavior of discrete interface growth models belonging to the Edwards--Wilkinson (EW) and Kardar--Parisi--Zhang (KPZ) universality classes, when defined on a complete graph, a topolโ€ฆ

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Computer Science Preprint PDF DOI

"It depends on where AI is used": Players' attitude patterns and evaluative logics toward different AI applications in digital games

Ting-Chen Hsu, Jiangxu Lin, Wenran Chen, Fei Qin, Zheyuan Zhang ยท 2026

As AI becomes increasingly embedded in digital games, players' attitudes de-pend not only on whether AI is used, but also on where and how it intervenes in gameplay. This study examines players' evaluโ€ฆ

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Computer Science Preprint PDF DOI

A Generalisation of Goursat's Algorithm for Integration in Finite Terms

Sam Blake ยท 2026

We give a self-contained, modern exposition of \'Edouard Goursat's 1887 theorem on pseudo-elliptic integrals -- those integrals of the form $\int F(t)\,\d t/\sqrt{R(t)}$ with $R$ a cubic or quartic poโ€ฆ

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Computer Science Preprint PDF DOI

Toward a Characterization of Simulation Between Arithmetic Theories

Hunter Monroe ยท 2026

We study when a sound arithmetic theory $\mathcal S{\supseteq}S^1_2$ with polynomial-time decidable axioms efficiently proves the bounded consistency statements $Con_{\mathcal S{+}\phi}(n)$ for a trueโ€ฆ

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Physics Preprint PDF DOI

Sampling two-dimensional spin systems with transformers

Piotr Bia{l}as, Piotr Korcyl, Tomasz Stebel, Adam Stefanski, Dawid Zapolski ยท 2026

Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transfโ€ฆ

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Earth & Environmental Sciences Preprint PDF DOI

Thermal instability and rocky planetesimal formation in the inner regions of protoplanetary disks

Ryo Kato, Takahiro Ueda, Satoshi Okuzumi ยท 2026

The inner regions of protoplanetary disks are promising formation sites of rocky planetesimals. Theoretical studies have proposed a scenario in which thermal ionization activates the magnetorotationalโ€ฆ

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AI & Data Science Preprint PDF DOI

Debiasing Reward Models via Causally Motivated Inference-Time Intervention

Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida ยท 2026

Reward models (RMs) play a central role in aligning large language models (LLMs) with human preferences. However, RMs are often sensitive to spurious features such as response length. Existing inferenโ€ฆ

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AI & Data Science Preprint PDF DOI

Toward Scalable SDN for LEO Mega-Constellations: A Graph Learning Approach

Sivaram Krishnan, Bassel Al Homssi, Zhouyou Gu, Jihong Park, Sung-Min Oh, Jinho Choi ยท 2026

Terrestrial network limitations drive the integration of non-terrestrial networks (NTNs), notably mega-constellations comprising thousands of low Earth orbit (LEO) satellites. While these satellites aโ€ฆ

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AI & Data Science Preprint PDF DOI

From Coarse to Fine: Benchmarking and Reward Modeling for Writing-Centric Generation Tasks

Qingyu Ren, Tianjun Pan, Xingzhou Chen, Xuhong Wang ยท 2026

Large language models have achieved remarkable progress in text generation but still struggle with generative writing tasks. In terms of evaluation, existing benchmarks evaluate writing reward models โ€ฆ

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Computer Science Preprint PDF DOI

Toward Autonomous SOC Operations: End-to-End LLM Framework for Threat Detection, Query Generation, and Resolution in Security Operations

Md Hasan Saju, Akramul Azim ยท 2026

Security Operations Centers (SOCs) face mounting operational challenges. These challenges come from increasing threat volumes, heterogeneous SIEM platforms, and time-consuming manual triage workflows.โ€ฆ

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AI & Data Science Preprint PDF DOI

Toward Personalized Digital Twins for Cognitive Decline Assessment: A Multimodal, Uncertainty-Aware Framework

Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang, Laura J. Brattain ยท 2026

Cognitive decline is highly heterogeneous across individuals, which complicates prognosis, trial design, and treatment planning. We present the Personalized Cognitive Decline Assessment Digital Twin (โ€ฆ

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AI & Data Science Preprint PDF DOI

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance

Jerry Y. Huang, Justin Lin, Sheel Shah, Kartik Nair, Nicholas M. Boffi ยท 2026

In generative modeling, we often wish to produce samples that maximize a user-specified reward such as aesthetic quality or alignment with human preferences, a problem known as guidance. Despite theirโ€ฆ

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Physics Preprint PDF DOI

Dwarf Galaxies Hosting Extreme Star-Forming Regions and (Variable) AGNs at Radio Wavelengths

John-Michael Eberhard, Amy E. Reines ยท 2026

We present a detailed study of radio-detected dwarf galaxies (with stellar masses less than 3 billion solar masses) to characterize extreme star formation and search for (variable) radio AGNs. Our samโ€ฆ

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AI & Data Science Preprint PDF DOI

AdvDMD: Adversarial Reward Meets DMD For High-Quality Few-Step Generation

Xu Wang, Zexian Li, Litong Gong, Tiezheng Ge, Zhijie Deng ยท 2026

Diffusion models offer superior generation quality at the expense of extensive sampling steps. Distillation methods, with Distribution Matching Distillation (DMD) as a popular example, can mitigate โ€ฆ

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Physics Preprint PDF DOI

SPHEREx Ultracool Dwarf spectral Atlas (SUDA): Atmospheric and Fundamental Parameters of Ultracool Dwarfs

Zhijun Tu, Shu Wang, Haomiao Huang, Xiaodian Chen, Jifeng Liu ยท 2026

We present the SPHEREx Ultracool Dwarf spectral Atlas (SUDA), a homogeneous sample of 1675 ultracool dwarfs with continuous 0.75--5 $\mu$m spectroscopy from SPHEREx QR2. Using the SAND and ATMO2020++ โ€ฆ

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AI & Data Science Preprint PDF DOI

GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents

GLM-V Team: Wenyi Hong, Xiaotao Gu, Ziyang Pan, Zhen Yang, Yuting Wang, Yue Wang, Yuanchang Yue, Yu Wang, Yanling Wang, Yan Wang, Xijun Liu, Wenmeng Yu, Weihan Wang, Wei Li, Shuaiqi Duan, Sheng Yang, Ruiliang Lv, Mingdao Liu, Lihang Pan, Ke Ning, Junhui Ji, Jinjiang Wang, Jing Chen, Jiazheng Xu, Jiale Zhu, Jiale Cheng, Ji Qi, Guobing Gan, Guo Wang, Cong Yao, Zijun Dou, Zihao Zhou, Zihan Wang, Zhiqi Ge, Zhijie Li, Zhenyu Hou, Zhao Xue, Zehui Wang, Zehai He, Yusen Liu, Yukuo Cen, Yuchen Li, Yuan Wang, Yijian Lu, Yanzi Wang, Yadong Xue, Xinyu Zhang, Xinyu Liu, Wenkai Li, Tianyu Tong, Tianshu Zhang, Shengdong Yan, Qinkai Zheng, Mingde Xu, Licheng Bao, Jiaxing Xu, Jiaxin Fan, Jiawen Qian, Jiali Chen, Jiahui Lin, Haozhi Zheng, Haoran Wang, Haochen Li, Fan Yang, Dan Zhang, Chuangxin Zhao, Chengcheng Wu, Boyan Shi, Bowei Jia, Baoxu Wang, Peng Zhang, Debing Liu, Bin Xu, Juanzi Li, Minlie Huang, Yuxiao Dong, Jie Tang ยท 2026

We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depends not only on languโ€ฆ

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