Tootfinder

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
Xuehui Wang, Zhenyu Wu, JingJing Xie, Zichen Ding, Bowen Yang, Zehao Li, Zhaoyang Liu, Qingyun Li, Xuan Dong, Zhe Chen, Weiyun Wang, Xiangyu Zhao, Jixuan Chen, Haodong Duan, Tianbao Xie, Chenyu Yang, Shiqian Su, Yue Yu, Yuan Huang, Yiqian Liu, Xiao Zhang, Yanting Zhang, Xiangyu Yue, Weijie Su, Xizhou Zhu, Wei Shen, Jifeng Dai, Wenhai Wang

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents
We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms. It comprises four levels: GUI Content Understanding, Element Grounding, Task Automation, and Task Collaboration, covering essential skills for GUI agents. In addition, we propose a novel Efficiency-Quality Area (EQA) metric to assess GUI agent execution efficiency in online automation scenarios. Through MMBench-GUI, we identify accurate visual gr…

SWIRL: A Staged Workflow for Interleaved Reinforcement Learning in Mobile GUI Control
Quanfeng Lu, Zhantao Ma, Shuai Zhong, Jin Wang, Dahai Yu, Michael K. Ng, Ping Luo
https://arxiv.org/abs/2508.20018 …

SWIRL: A Staged Workflow for Interleaved Reinforcement Learning in Mobile GUI Control
The rapid advancement of large vision language models (LVLMs) and agent systems has heightened interest in mobile GUI agents that can reliably translate natural language into interface operations. Existing single-agent approaches, however, remain limited by structural constraints. Although multi-agent systems naturally decouple different competencies, recent progress in multi-agent reinforcement learning (MARL) has often been hindered by inefficiency and remains incompatible with current LVLM a…

Quantitative stability for the conformally invariant Chang-Gui inequality on the exponentiation of functions on the sphere
Monideep Ghosh, Debabrata Karmakar
https://arxiv.org/abs/2508.19930

Quantitative stability for the conformally invariant Chang-Gui inequality on the exponentiation of functions on the sphere
In this work, we focus on a recent variant of the Trudinger-Moser-Onofri inequality introduced by S. Y. Alice Chang and Changfeng Gui \cite{CG-2023}: \begin{align*} α\int_{\mathbb{S}^2}|\nabla_{\mathbb{S}^2}u|^2 {\rm d}ω+2 \int_{\mathbb{S}^2} u {\rm d}ω-\frac{1}{2}\ln\left[\left(\int_{\mathbb{s}^2}e^{2u}{\rm d}ω\right)^2-\sum_{i=1}^3\left(\int_{\mathbb{s}^2}ω_i e^{2u}{\rm d} ω\right)^2\right] \geq 0 \end{align*} holds on $H^1(\mathbb{S}^2)$ if and only if $α\geq \frac{2}{3}$. I…

Weekend list of critical reading links about the state[1] of Tech, AI[2] hype/finance/politics, mostly long form:
Ed Zitron's The Hater's Guide To The AI Bubble
https://www.wheresyoured.at/the-haters-gui/
How to use computing power faster: on the weird ec…

The Hater's Guide To The AI Bubble
Hey! Before we go any further — if you want to support my work, please sign up for the premium version of Where’s Your Ed At, it’s a $7-a-month (or $70-a-year) paid product where every week you get a premium newsletter, all while supporting my free work too.  Also,

Say about Linux what you will, but getting this much detail about what your graphics card is doing is pretty cool.🐧
`amdgpu_top --gui`
#Linux #LinuxGaming #GamingOnLinux

If you just need a pretty figure from a dataset and not the full power of R, have a look at #gui

Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
Tian-Yu Xiang, Ao-Qun Jin, Xiao-Hu Zhou, Mei-Jiang Gui, Xiao-Liang Xie, Shi-Qi Liu, Shuang-Yi Wang, Sheng-Bin Duan, Fu-Chao Xie, Wen-Kai Wang, Si-Cheng Wang, Ling-Yun Li, Tian Tu, Zeng-Guang Hou
https://arxiv.org/abs/2506.20966…

Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
Vision-language-action (VLA) models extend vision-language models (VLM) by integrating action generation modules for robotic manipulation. Leveraging strengths of VLM in vision perception and instruction understanding, VLA models exhibit promising generalization across diverse manipulation tasks. However, applications demanding high precision and accuracy reveal performance gaps without further adaptation. Evidence from multiple domains highlights the critical role of post-training to align fou…

Euphonica is a Rust-Powered MPD Client Heavy on Bling
MPD (Music Player Daemon) is a server-client audio player long popular with Linux users. The headless daemon runs as a background service, typically on a remote audio server. Music is then accessed via a GUI client frontend, which connects to the MPD server to stream content.
🎶

Euphonica is a Rust-Powered MPD Client Heavy on Bling
Euphonica is a new Rust-based MPD frontend for Linux desktops, with 'bling' as a key feature. I showcase its design, features, and current development status.

GUI zum Nacherleben: Website emuliert Einstellungen zahlreicher Macs
Wie hat man Macs früher konfiguriert? Der Designer Marcin Wichery hat 20 Jahre macOS-Geschichte auf einer Seite zusammengetragen.
http…

https://www.wheresyoured.at/the-haters-gui/

The Hater's Guide To The AI Bubble
Hey! Before we go any further — if you want to support my work, please sign up for the premium version of Where’s Your Ed At, it’s a $7-a-month (or $70-a-year) paid product where every week you get a premium newsletter, all while supporting my free work too.  Also,

Replaced article(s) found for eess.IV. https://arxiv.org/list/eess.IV/new
[1/1]:
- MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation
Huang, Zhou, Gui, Xie, Liu, Wang, Feng, Lai, Hou

Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Yi Xu, Yesheng Zhang, jiajia Liu, Jingdong Chen
https://arxiv.org/abs/2508.16271 https:/…

Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Multimodal large language models (MLLMs) have emerged as pivotal tools in enhancing human-computer interaction. In this paper we focus on the application of MLLMs in the field of graphical user interface (GUI) elements structuring, where they assist in processing user instructions based on screen contents. Despite the promise of MLLMs, their performance in precisely generating UI element coordinates, a critical aspect of GUI understanding, is hindered by the nature of next-token prediction trai…

Mobile-Agent-v3: Foundamental Agents for GUI Automation
Jiabo Ye, Xi Zhang, Haiyang Xu, Haowei Liu, Junyang Wang, Zhaoqing Zhu, Ziwei Zheng, Feiyu Gao, Junjie Cao, Zhengxi Lu, Jitong Liao, Qi Zheng, Fei Huang, Jingren Zhou, Ming Yan
https://arxiv.org/abs/2508.15144

Mobile-Agent-v3: Foundamental Agents for GUI Automation
This paper introduces GUI-Owl, a foundational GUI agent model that achieves state-of-the-art performance among open-source end-to-end models on ten GUI benchmarks across desktop and mobile environments, covering grounding, question answering, planning, decision-making, and procedural knowledge. GUI-Owl-7B achieves 66.4 on AndroidWorld and 29.4 on OSWorld. Building on this, we propose Mobile-Agent-v3, a general-purpose GUI agent framework that further improves performance to 73.3 on AndroidWorld…

My main problem with @edzitron.com 's piece on the #AIbubble is that I agree with so much of it.
I'm now wondering if I've missed something about #LLMs? The numbers and implications for stock markets are terrifyingly huge!
https://www.wheresyoured.at/the-haters-gui/

CachyOS is all the rage.
CachyOS is indeed very fast, even on this underpowered Chromebook.
It is also kinda broken.
The installer is so close to unusable (as in, it's a GUI, but the mouse cursor doesn't curse and the display brightness is pegged at minimum and can't be controlled) that I very nearly gave up. Installing Arch on the CLI is far faster.
Wayland is irritating, the font rendering is still fucked (text literally jiggles around on screen!) and the s…

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
Tao Guo, Junxiao Wang, Fushuo Huo, Laizhong Cui, Song Guo, Jie Gui, Dacheng Tao
https://arxiv.org/abs/2508.16261

On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
Federated Learning (FL) enables training models across decentralized data silos while preserving client data privacy. Recent research has explored efficient methods for post-training large language models (LLMs) within FL to address computational and communication challenges. While existing approaches often rely on access to LLMs' internal information, which is frequently restricted in real-world scenarios, an inference-only paradigm (black-box FedLLM) has emerged to address these limitations. …

Chain-of-Memory: Enhancing GUI Agents for Cross-Application Navigation
Xinzge Gao, Chuanrui Hu, Bin Chen, Teng Li
https://arxiv.org/abs/2506.18158 https://…

Chain-of-Memory: Enhancing GUI Agents for Cross-Application Navigation
Multimodal large language models (MLLMs) are attracting growing attention in the development of Graphical User Interface (GUI) agents. Existing approaches often rely on historical screenshots or actions to implicitly represent the task state. This reliance poses challenges for GUI agents in accurately understanding task states and underscores the absence of effective mechanisms to store critical information in complex and lengthy cross-app tasks. To address these challenges, we propose Chain-of…

Self-organization drives symmetry-breaking, scaling, and critical growth transitions in stem cell-derived organoids
Daniel Aguilar-Hidalgo, Joel Ostblom, M Mona Siu, Divy Raval, Ajinkya Ghagre, Tiam Heydari, Benjamin McMaster, Jonathan Gui, Nicolas Werschler, Mukul Tewary, Peter W. Zandstra
https://arxiv.org/abs/2507.18887

Self-organization drives symmetry-breaking, scaling, and critical growth transitions in stem cell-derived organoids
The emergence of spatial patterns and organized growth is a hallmark of developing tissues. While symmetry-breaking and scaling laws govern these processes, how cells coordinate spatial patterning with size regulation remains unclear. Here, we combine quantitative imaging, a Turing activator-repressor model with self-organized reactive boundaries, and in vitro models of early mouse development to study mesodermal pattern formation in two-dimensional (2D) gastruloids. We show that colony size di…

MagicGUI: A Foundational Mobile GUI Agent with Scalable Data Pipeline and Reinforcement Fine-tuning
Liujian Tang, Shaokang Dong, Yijia Huang, Minqi Xiang, Hongtao Ruan, Bin Wang, Shuo Li, Zhihui Cao, Hailiang Pang, Heng Kong, He Yang, Mingxu Chai, Zhilin Gao, Xingyu Liu, Yingnan Fu, Jiaming Liu, Tao Gui, Xuanjing Huang, Yu-Gang Jiang, Qi Zhang, Kang Wang, Yunke Zhang, Yuran Wang

MagicGUI: A Foundational Mobile GUI Agent with Scalable Data Pipeline and Reinforcement Fine-tuning
This paper presents MagicGUI, a foundational mobile GUI agent designed to address critical challenges in perception, grounding, and reasoning within real-world mobile GUI environments. The framework is underpinned by following six key components: (1) a comprehensive and accurate dataset, constructed via the scalable GUI Data Pipeline, which aggregates the largest and most diverse GUI-centric multimodal data to date from open-source repositories, automated crawling, and targeted manual annotatio…

You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation
Yutong Bian, Xianhao Lin, Yupeng Xie, Tianyang Liu, Mingchen Zhuge, Siyuan Lu, Haoming Tang, Jinlin Wang, Jiayi Zhang, Jiaqi Chen, Xiangru Tang, Yongxin Ni, Sirui Hong, Chenglin Wu
https://arxiv.org/abs/2508.14104

You Don't Know Until You Click:Automated GUI Testing for Production-Ready Software Evaluation
Large Language Models (LLMs) and code agents in software development are rapidly evolving from generating isolated code snippets to producing full-fledged software applications with graphical interfaces, interactive logic, and dynamic behaviors. However, current benchmarks fall short in evaluating such production-ready software, as they often rely on static checks or binary pass/fail scripts, failing to capture the interactive behaviors and runtime dynamics that define real-world usability - qu…

Finite-size security analysis for quantum protocols: A Python framework using the Entropy Accumulation Theorem with graphical interface
Piotr Mironowicz, Mohamed Bourennane
https://arxiv.org/abs/2506.18888

Finite-size security analysis for quantum protocols: A Python framework using the Entropy Accumulation Theorem with graphical interface
We present a comprehensive software framework for the finite-size security analysis of quantum random number generation (QRNG) and quantum key distribution (QKD) protocols, based on the Entropy Accumulation Theorem (EAT). Our framework includes both a Python API and an intuitive graphical user interface (GUI), designed to support protocol designers and experimentalists in certifying randomness and key rates under realistic, finite-resource conditions. At its core, the framework automates the co…

How to search successfully in Spotlight: GUI tools #Finder

How to search successfully in Spotlight: GUI tools
Using the Spotlight window and Finder’s Find window to locate local files that match your search criteria. Word boundaries and their effect on search results.

OH GOD SOMEONE SEND HELP I'VE STARTED LEARNING HOW TO TRACKER AGAIN
#genesis #ym2612 #furnace #tracker

Non-holomorphic modular flavor symmetry and odd weight polyharmonic Maa{\ss} form
Bu-Yao Qu, Jun-Nan Lu, Gui-Jun Ding
https://arxiv.org/abs/2506.19822 http…

Non-holomorphic modular flavor symmetry and odd weight polyharmonic Maaß form
We extend the framework of non-holomorphic modular flavor symmetry to include the odd weight polyharmonic Maaß forms. The integer weight polyharmonic Maaß forms of level $N$ can be arranged into multipltets of the homogeneous finite modular group $Γ'_N$. We propose to construct the integer weight, including weight one, non-holomorphic polyharmonic Maaß forms from the non-holomorphic Eisenstein series. The previous results of even weight polyharmonic Maaß forms are reproduced. We apply this…

LaSM: Layer-wise Scaling Mechanism for Defending Pop-up Attack on GUI Agents
Zihe Yan, Zhuosheng Zhang
https://arxiv.org/abs/2507.10610 https://

LaSM: Layer-wise Scaling Mechanism for Defending Pop-up Attack on GUI Agents
Graphical user interface (GUI) agents built on multimodal large language models (MLLMs) have recently demonstrated strong decision-making abilities in screen-based interaction tasks. However, they remain highly vulnerable to pop-up-based environmental injection attacks, where malicious visual elements divert model attention and lead to unsafe or incorrect actions. Existing defense methods either require costly retraining or perform poorly under inductive interference. In this work, we systemati…

🇺🇦 Auf radioeins läuft...
Sam Taylor-Wood:
🎵 I'm In Love With A German Film Star
#NowPlaying #SamTaylorWood
https://kompakt.bandcamp.com/track/im-in-love-with-a-german-film-star-gui-boratto-remix
https://open.spotify.com/track/3NT7jidpDWSaiZe73A5nRs

Replaced article(s) found for cs.SD. https://arxiv.org/list/cs.SD/new
[1/1]:
- Koel-TTS: Enhancing LLM based Speech Generation with Preference Alignment and Classifier Free Gui...
Hussain, Neekhara, Yang, Casanova, Ghosh, Desta, Fejgin, Valle, Li

Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents
Jinjie Wei, Jiyao Liu, Lihao Liu, Ming Hu, Junzhi Ning, Mingcheng Li, Weijie Yin, Junjun He, Xiao Liang, Chao Feng, Dingkang Yang
https://arxiv.org/abs/2506.17913

Learning, Reasoning, Refinement: A Framework for Kahneman's Dual-System Intelligence in GUI Agents
Graphical User Interface (GUI) agents have made significant progress in automating digital tasks through the utilization of computer vision and language models. Nevertheless, existing agent systems encounter notable limitations. Firstly, they predominantly depend on trial and error decision making rather than progressive reasoning, thereby lacking the capability to learn and adapt from interactive encounters. Secondly, these systems are assessed using overly simplistic single step accuracy metr…

VisualTrap: A Stealthy Backdoor Attack on GUI Agents via Visual Grounding Manipulation
Ziang Ye, Yang Zhang, Wentao Shi, Xiaoyu You, Fuli Feng, Tat-Seng Chua
https://arxiv.org/abs/2507.06899

VisualTrap: A Stealthy Backdoor Attack on GUI Agents via Visual Grounding Manipulation
Graphical User Interface (GUI) agents powered by Large Vision-Language Models (LVLMs) have emerged as a revolutionary approach to automating human-machine interactions, capable of autonomously operating personal devices (e.g., mobile phones) or applications within the device to perform complex real-world tasks in a human-like manner. However, their close integration with personal devices raises significant security concerns, with many threats, including backdoor attacks, remaining largely unexp…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[5/5]:
- GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding
Tang, Gu, Lu, Liu, Shen, Meng, Wang, Zhang, Shen, Lu, Xiao, Zhuang

CRAFT-GUI: Curriculum-Reinforced Agent For GUI Tasks
Songqin Nong, Jingxuan Xu, Sheng Zhou, Jianfeng Chen, Xiaoxuan Tang, Tao Jiang, Wenhao Xu
https://arxiv.org/abs/2508.11360 h…

CRAFT-GUI: Curriculum-Reinforced Agent For GUI Tasks
As autonomous agents become adept at understanding and interacting with graphical user interface (GUI) environments, a new era of automated task execution is emerging. Recent studies have demonstrated that Reinforcement Learning (RL) can effectively enhance agents' performance in dynamic interactive GUI environments. However, these methods face two key limitations: (1) they overlook the significant variation in difficulty across different GUI tasks by treating the entire training data as a unif…

Hear Your Code Fail, Voice-Assisted Debugging for Python
Sayed Mahbub Hasan Amiri, Md. Mainul Islam, Mohammad Shakhawat Hossen, Sayed Majhab Hasan Amiri, Mohammad Shawkat Ali Mamun, Sk. Humaun Kabir, Naznin Akter
https://arxiv.org/abs/2507.15007

Hear Your Code Fail, Voice-Assisted Debugging for Python
This research introduces an innovative voice-assisted debugging plugin for Python that transforms silent runtime errors into actionable audible diagnostics. By implementing a global exception hook architecture with pyttsx3 text-to-speech conversion and Tkinter-based GUI visualization, the solution delivers multimodal error feedback through parallel auditory and visual channels. Empirical evaluation demonstrates 37% reduced cognitive load (p<0.01, n=50) compared to traditional stack-trace debugg…

MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment
Yucheng Shi, Wenhao Yu, Zaitang Li, Yonglin Wang, Hongming Zhang, Ninghao Liu, Haitao Mi, Dong Yu
https://arxiv.org/abs/2507.05720

MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment
Recently, there has been a surge of vision-based GUI agents designed to automate everyday mobile and web tasks. These agents interpret raw GUI screenshots and autonomously decide where to click, scroll, or type, which bypasses handcrafted rules and app-specific APIs. However, most existing methods trained GUI agent in the offline environment using pre-collected trajectories. This approach limits scalability, causes overfitting to specific UI templates, and leads to brittle policies when faced w…

Radio emission from airplanes as observed with RNO-G
G Collaboration, S. Agarwal, J. A. Aguilar, N. Alden, S. Ali, P. Allison, M. Betts, D. Besson, A. Bishop, O. Botner, S. Bouma, S. Buitink, R. Camphyn, J. Chan, S. Chiche, B. A. Clark, A. Coleman, K. Couberly, S. de Kockere, K. D. de Vries, C. Deaconu, P. Giri, C. Glaser, T. Gl\"usenkamp, H. Gui, A. Hallgren, S. Hallmann, J. C. Hanson, K. Helbing, B. Hendricks, J. Henrichs, N. Heyer, C. Hornhuber, E. Huesca Santiago, K. Hughes, A…

Radio emission from airplanes as observed with RNO-G
This paper describes how intentional and unintentional radio emission from airplanes is recorded with the Radio Neutrino Observatory Greenland (RNO-G). We characterize the received signals and define a procedure to extract a clean set of impulsive signals. These signals are highly suitable for instrument calibration, also for future experiments. A set of signals is used to probe the timing precision of RNO-G in-situ, which is found to match expectations. We also discuss the impact of these sign…

GUI-ReRank: Enhancing GUI Retrieval with Multi-Modal LLM-based Reranking
Kristian Kolthoff, Felix Kretzer, Christian Bartelt, Alexander Maedche, Simone Paolo Ponzetto
https://arxiv.org/abs/2508.03298

GUI-ReRank: Enhancing GUI Retrieval with Multi-Modal LLM-based Reranking
GUI prototyping is a fundamental component in the development of modern interactive systems, which are now ubiquitous across diverse application domains. GUI prototypes play a critical role in requirements elicitation by enabling stakeholders to visualize, assess, and refine system concepts collaboratively. Moreover, prototypes serve as effective tools for early testing, iterative evaluation, and validation of design ideas with both end users and development teams. Despite these advantages, the…

I've managed to install the Stirling PDF tools on one of our company's mini PCs using #podman. I've tried doing it with Redhat's cockpit admin GUI but it didn't really work, probably because of SELinux or something (it's always SELinux...). I found some instruction for the commandline that worked.
This is all seems like a good use-case for Docker but the whole contain…

Tonight I had my first longer #VibeCoding session using #Aider. The result is a significantly improved UX for #SPOV (a

Giant Magneto-Optical Effects in Two-Dimensional Flat-Band Antiferromagnets
Ping Yang, Wanxiang Feng, Siyuan Liu, Shan Guan, Liwei Wen, Wei Jiang, Gui-Bin Liu, Yugui Yao
https://arxiv.org/abs/2506.16749

Giant Magneto-Optical Effects in Two-Dimensional Flat-Band Antiferromagnets
In this work, we reveal giant magneto-optical responses in two-dimensional(2D) antiferromagnets with nearly flat electronic bands, based on first-principles calculations and group-theoretical analysis. We identify a record-large second-order magneto-optical Schafer-Hubert(SH) effect, featuring a polarization rotation angle of 28 degree, in monolayer antiferromagnetic RuOCl2, driven by flatband-enhanced interband optical transitions. Both the valence and conduction bands exhibit pronounced direc…

ACS: An interactive framework for conformal selection
Yu Gui, Ying Jin, Yash Nair, Zhimei Ren
https://arxiv.org/abs/2507.15825 https://

ACS: An interactive framework for conformal selection
This paper presents adaptive conformal selection (ACS), an interactive framework for model-free selection with guaranteed error control. Building on conformal selection (Jin and Candès, 2023b), ACS generalizes the approach to support human-in-the-loop adaptive data analysis. Under the ACS framework, we can partially reuse the data to boost the selection power, make decisions on the fly while exploring the data, and incorporate new information or preferences as they arise. The key to ACS is a c…

GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
Jingqi Yang, Zhilong Song, Jiawei Chen, Mingli Song, Sheng Zhou, linjun sun, Xiaogang Ouyang, Chun Chen, Can Wang
https://arxiv.org/abs/2506.14477

GUI-Robust: A Comprehensive Dataset for Testing GUI Agent Robustness in Real-World Anomalies
The development of high-quality datasets is crucial for benchmarking and advancing research in Graphical User Interface (GUI) agents. Despite their importance, existing datasets are often constructed under idealized conditions, overlooking the diverse anomalies frequently encountered in real-world deployments. To address this limitation, we introduce GUI-Robust, a novel dataset designed for comprehensive GUI agent evaluation, explicitly incorporating seven common types of anomalies observed in …

This https://arxiv.org/abs/2504.17934 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Toward a Human-Centered Evaluation Framework for Trustworthy LLM-Powered GUI Agents
The rise of Large Language Models (LLMs) has revolutionized Graphical User Interface (GUI) automation through LLM-powered GUI agents, yet their ability to process sensitive data with limited human oversight raises significant privacy and security risks. This position paper identifies three key risks of GUI agents and examines how they differ from traditional GUI automation and general autonomous agents. Despite these risks, existing evaluations focus primarily on performance, leaving privacy an…

How to use SDKMAN with MobaXterm on Win11: https://blog.rmendes.net/2025/07/11/how-to-use-sdkman-with.html

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
Abhinav Chalise, Nimesh Gopal Pradhan, Nishan Khanal, Prashant Raj Bista, Dinesh Baniya Kshatri
https://arxiv.org/abs/2508.12469 …

Mechanical Automation with Vision: A Design for Rubik's Cube Solver
The core mechanical system is built around three stepper motors for physical manipulation, a microcontroller for hardware control, a camera and YOLO detection model for real-time cube state detection. A significant software component is the development of a user-friendly graphical user interface (GUI) designed in Unity. The initial state after detection from real-time YOLOv8 model (Precision 0.98443, Recall 0.98419, Box Loss 0.42051, Class Loss 0.2611) is virtualized on GUI. To get the solution…

RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution
Haodong He, Yancheng Bai, Rui Lan, Xu Duan, Lei Sun, Xiangxiang Chu, Gui-Song Xia
https://arxiv.org/abs/2508.16158

RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution
The rich textual information of large vision-language models (VLMs) combined with the powerful generative prior of pre-trained text-to-image (T2I) diffusion models has achieved impressive performance in single-image super-resolution (SISR). However, existing methods still face significant challenges in generating clear and accurate regional details, particularly in scenarios involving multiple objects. This challenge primarily stems from a lack of fine-grained regional descriptions and the mode…

Multimode Fiber Imaging Based on Hydrogel Fiber
Lele He, Mengchao Cao, Lili Gui, Jingjing Guo, Xiaosheng Xiao
https://arxiv.org/abs/2508.14501 https://arxi…

Multimode Fiber Imaging Based on Hydrogel Fiber
We demonstrate a multimode fiber imaging technique based on hydrogel fibers, which are suitable for biomedical applications owing to their biocompatibility and environmental friendliness. High-resolution handwritten images are successfully recovered by utilizing a Pix2Pix image generation network.

Computational Studies in Influencer Marketing: A Systematic Literature Review
Haoyang Gui, Thales Bertaglia, Catalina Goanta, Gerasimos Spanakis
https://arxiv.org/abs/2506.14602

Computational Studies in Influencer Marketing: A Systematic Literature Review
Influencer marketing has become a crucial feature of digital marketing strategies. Despite its rapid growth and algorithmic relevance, the field of computational studies in influencer marketing remains fragmented, especially with limited systematic reviews covering the computational methodologies employed. This makes overarching scientific measurements in the influencer economy very scarce, to the detriment of interested stakeholders outside of platforms themselves, such as regulators, but also…

Replaced article(s) found for math.QA. https://arxiv.org/list/math.QA/new
[1/1]:
- On a Connes Fusion Approach to Finite Index Extensions of Conformal Nets
Bin Gui

Efficient GPU-Centered Singular Value Decomposition Using the Divide-and-Conquer Method
Shifang Liu, Huiyuan Li, Hongjiao Sheng, Haoyuan Gui, Xiaoyu Zhang
https://arxiv.org/abs/2508.11467

Efficient GPU-Centered Singular Value Decomposition Using the Divide-and-Conquer Method
Singular Value Decomposition (SVD) is a fundamental matrix factorization technique in linear algebra, widely applied in numerous matrix-related problems. However, traditional SVD approaches are hindered by slow panel factorization and frequent CPU-GPU data transfers in heterogeneous systems, despite advancements in GPU computational capabilities. In this paper, we introduce a GPU-centered SVD algorithm, incorporating a novel GPU-based bidiagonal divide-and-conquer (BDC) method. We reformulate t…

V2P: From Background Suppression to Center Peaking for Robust GUI Grounding Task
Jikai Chen, Long Chen, Dong Wang, Leilei Gan, Chenyi Zhuang, Jinjie Gu
https://arxiv.org/abs/2508.13634

V2P: From Background Suppression to Center Peaking for Robust GUI Grounding Task
Precise localization of GUI elements is crucial for the development of GUI agents. Traditional methods rely on bounding box or center-point regression, neglecting spatial interaction uncertainty and visual-semantic hierarchies. Recent methods incorporate attention mechanisms but still face two key issues: (1) ignoring processing background regions causes attention drift from the desired area, and (2) uniform labeling fails to distinguish between center and edges of the target UI element, leadin…

Hijacking JARVIS: Benchmarking Mobile GUI Agents against Unprivileged Third Parties
Guohong Liu, Jialei Ye, Jiacheng Liu, Yuanchun Li, Wei Liu, Pengzhi Gao, Jian Luan, Yunxin Liu
https://arxiv.org/abs/2507.04227

Hijacking JARVIS: Benchmarking Mobile GUI Agents against Unprivileged Third Parties
Mobile GUI agents are designed to autonomously execute diverse device-control tasks by interpreting and interacting with mobile screens. Despite notable advancements, their resilience in real-world scenarios where screen content may be partially manipulated by untrustworthy third parties remains largely unexplored. Owing to their black-box and autonomous nature, these agents are vulnerable to manipulations that could compromise user devices. In this work, we present the first systematic investi…

Replaced article(s) found for math.OA. https://arxiv.org/list/math.OA/new
[1/1]:
- On a Connes Fusion Approach to Finite Index Extensions of Conformal Nets
Bin Gui

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization
Jiaqi Tang, Yu Xia, Yi-Feng Wu, Yuwei Hu, Yuhui Chen, Qing-Guo Chen, Xiaogang Xu, Xiangyu Wu, Hao Lu, Yanqing Ma, Shiyin Lu, Qifeng Chen
https://arxiv.org/abs/2506.09373

LPO: Towards Accurate GUI Agent Interaction via Location Preference Optimization
The advent of autonomous agents is transforming interactions with Graphical User Interfaces (GUIs) by employing natural language as a powerful intermediary. Despite the predominance of Supervised Fine-Tuning (SFT) methods in current GUI agents for achieving spatial localization, these methods face substantial challenges due to their limited capacity to accurately perceive positional data. Existing strategies, such as reinforcement learning, often fail to assess positional accuracy effectively, …

Ants3 toolkit: front-end for Geant4 with interactive GUI and Python scripting
A. Morozov, L. M. S. Margato, G. Canezin, J. Gonzalez
https://arxiv.org/abs/2506.07922

Ants3 toolkit: front-end for Geant4 with interactive GUI and Python scripting
Ants3 is a toolkit that serves as a front-end for particle simulations in Geant4 and offers a custom simulator for optical photons. It features a fully interactive Graphical User Interface and an extensive scripting system based on general-purpose scripting languages (Python and JavaScript). Ants3 covers the entire detector simulation/optimization cycle, providing an intuitive approach for configuration of the geometry and simulation conditions, the possibility to automatically distribute workl…

Non-Equilibrium Criticality-Enhanced Quantum Sensing with Superconducting Qubits
Hao Li, Yaoling Yang, Yun-Hao Shi, Zheng-An Wang, Ziting Wang, Jintao Li, Yipeng Zhang, Kui Zhao, Yue-Shan Xu, Cheng-Lin Deng, Yu Liu, Wei-Guo Ma, Tian-Ming Li, Jia-Chi Zhang, Cai-Ping Fang, Jia-Cheng Song, Hao-Tian Liu, Si-Yun Zhou, Zheng-He Liu, Bing-Jie Chen, Gui-Han Liang, Xiaohui Song, Zhongcheng Xiang, Kai Xu, Kaixuan Huang, Abolfazl Bayat, Heng Fan

Non-Equilibrium Criticality-Enhanced Quantum Sensing with Superconducting Qubits
Exploiting quantum features allows for estimating external parameters with precisions well beyond the capacity of classical sensors, a phenomenon known as quantum-enhanced precision. Quantum criticality has been identified as a resource for achieving such enhancements with respect to the probe size. However, they demand complex probe preparation and measurement and the achievable enhancement is ultimately restricted to narrow parameter regimes. On the other hand, non-equilibrium probes harness …

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
Fengxian Ji, Jingpu Yang, Zirui Song, Yuanxi Wang, Zhexuan Cui, Yuke Li, Qian Jiang, Miao Fang, Xiuying Chen
https://arxiv.org/abs/2508.09241

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing daily tasks through natural language instructions. However, current evaluation frameworks for GUI agents suffer from fundamental flaws: existing benchmarks overly focus on coarse-grained task completion while neglecting fine-grained control capabilities crucial for real-world applications. To address this, we introduc…

first time I’ve ever seen a GUI login screen for #FreeBSD. Which I've been using for ~30 years. https://infosec.exchange/@shodansafari/114783525879140775

Temac: Multi-Agent Collaboration for Automated Web GUI Testing
Chenxu Liu, Zhiyu Gu, Guoquan Wu, Ying Zhang, Jun Wei, Tao Xie
https://arxiv.org/abs/2506.00520

Temac: Multi-Agent Collaboration for Automated Web GUI Testing
Quality assurance of web applications is critical, as web applications play an essential role in people's daily lives. To reduce labor costs, automated web GUI testing (AWGT) is widely adopted, exploring web applications via GUI actions such as clicks and text inputs. However, these approaches face limitations in generating continuous and meaningful action sequences capable of covering complex functionalities. Recent work incorporates large language models (LLMs) for GUI testing. However, these…

SPAN: A cross-platform Python GUI software for optical and near-infrared spectral analysis
Daniele Gasparri, Lorenzo Morelli, Umberto Battino, Jairo M\'endez Abreu, Adriana de Lorenzo-C\'aceres
https://arxiv.org/abs/2508.01923

SPAN: A cross-platform Python GUI software for optical and near-infrared spectral analysis
The increasing availability of high-quality optical and near-infrared spectroscopic data, as well as advances in modelling techniques, have greatly expanded the scientific potential of spectroscopic studies. However, the software tools needed to fully exploit this potential often remain fragmented across multiple specialised packages, requiring scripting skills and manual integration to handle complex workflows. In this paper we present SPAN (SPectral ANalysis), a cross-platform, Python-based G…

VeriGUI: Verifiable Long-Chain GUI Dataset
Shunyu Liu, Minghao Liu, Huichi Zhou, Zhenyu Cui, Yang Zhou, Yuhao Zhou, Wendong Fan, Ge Zhang, Jiajun Shi, Weihao Xuan, Jiaxing Huang, Shuang Luo, Fang Wu, Heli Qi, Qingcheng Zeng, Ziqi Ren, Jialiang Gao, Jindi Lv, Junjie Wang, Aosong Feng, Heng Zhou, Wangchunshu Zhou, Zhenfei Yin, Wenlong Zhang, Guohao Li, Wenhao Yu, Irene Li, Lei Ma, Lei Bai, Qunshu Lin, Mingli Song, Dacheng Tao

VeriGUI: Verifiable Long-Chain GUI Dataset
Recent studies have delved into constructing autonomous agents capable of performing complex Graphical User Interface (GUI)-based computer tasks, with the potential to revolutionize human-computer interaction. Despite encouraging results, existing efforts mainly focus on short-term interactions and rely on outcome-only verification, thereby limiting their scalability in real-world GUI applications that demand long-horizon task decomposition and execution. In this work, we introduce VeriGUI, a n…

A simple GUI-based screencast demo of the @… AI Layer (OPAL), showing what’s now possible via MCP A2A—namely, composing and orchestrating agentic workflows through loosely coupled software.
How?
An Agent Host routes tasks to Agents via A2A. Agents then invoke MCP-accessible tools (functions, procedures, APIs) described using JSON/YAML and exposed …

I never imagined getting used to a new #HPC infrastructure would be such a pain.
I got used to cli, ssh access, bash scrips before, but suddenly everything is handled via a GUI, everything is containerized.
AND ALL MY WORKFLOWS ARE BROKEN!
I don't even manage to set up a simple #conda environment.

On reflection, I think the big mistake is the conflation of #AI with #LLM and #MachineLearning.
There are genuine exciting advances in ML with applications all over the place, in science, (not least in my own research group looking at high resolution regional climate downscaling), health diagnostics, defence etc. But these are not the AIs that journalists are talking about, nor that are really related the LLMs.
They're still good uses of GPUs and will probably produce economic benefits, but probably not the multi- trillion ones the pundits seem to be expecting
#AIbubble is that I agree with so much of it.
I'm now wondering if I've missed something about #LLMs? The numbers and implications for stock markets are terrifyingly huge!
https://www.wheresyoured.at/the-haters-gui/

It's useful that there's the possibility to add #gnd ids to #zenodo as well (in case creators don't have an #orcid). I wish it'd be clearer from the GUI that the required input format is …

Since DJV went into a hiatus, I have tried #mrv2 more than once but it wouldn't do. Brought down my whole Linux desktop last time I tried, just by showing/hiding certain parts of the GUI.
So I've compiled #OpenRV but I really want something that loads faster than that clunky old player (even…

Crosslisted article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Efficient GPU-Centered Singular Value Decomposition Using the Divide-and-Conquer Method
Shifang Liu, Huiyuan Li, Hongjiao Sheng, Haoyuan Gui, Xiaoyu Zhang

Test-Time Reinforcement Learning for GUI Grounding via Region Consistency
Yong Du, Yuchen Yan, Fei Tang, Zhengxi Lu, Chang Zong, Weiming Lu, Shengpei Jiang, Yongliang Shen
https://arxiv.org/abs/2508.05615

Test-Time Reinforcement Learning for GUI Grounding via Region Consistency
Graphical User Interface (GUI) grounding, the task of mapping natural language instructions to precise screen coordinates, is fundamental to autonomous GUI agents. While existing methods achieve strong performance through extensive supervised training or reinforcement learning with labeled rewards, they remain constrained by the cost and availability of pixel-level annotations. We observe that when models generate multiple predictions for the same GUI element, the spatial overlap patterns revea…

LLM-Guided Scenario-based GUI Testing
Shengcheng Yu, Yuchen Ling, Chunrong Fang, Quan Zhou, Chunyang Chen, Shaomin Zhu, Zhenyu Chen
https://arxiv.org/abs/2506.05079

LLM-Guided Scenario-based GUI Testing
The assurance of mobile app GUI is more and more significant. Automated GUI testing approaches of different strategies have been developed, while there are still huge gaps between the approaches and the app business logic, not taking the completion of specific testing scenarios as the exploration target, leading to the exploration missing of critical app functionalities. Learning from the manual testing, which takes testing scenarios with app business logic as the basic granularity, in this pap…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/3]:
- Compression Hacking: A Supplementary Perspective on Informatics Properties of Language Models fro...
Zang, Ning, Wei, Dou, Zhang, Mo, Li, Gui, Zhang, Huang

Efficient Third-Harmonic Generation via Strong Coupling of Quasi-Guided Modes
Xin Huang, Qi Lin, Sheng-Xuan Xia, Xiang Zhai, Gui-Dong Liu
https://arxiv.org/abs/2508.14514 https:…

Efficient Third-Harmonic Generation via Strong Coupling of Quasi-Guided Modes
Improving the conversion efficiency is critical for advancing nonlinear photonic devices, enabling applications in ultrafast optics, quantum light sources, and high-resolution imaging. Herein, we present a bilayer waveguide integrated with a periodic square nanocube array to enhance third-harmonic generation (THG) efficiency. This structure achieves strong coupling between TE- and TM-polarized quasi-guided mode (QGM) resonances, thereby enabling simultaneous dynamic control of both resonant Q-f…

Understanding Data Influence with Differential Approximation
Haoru Tan, Sitong Wu, Xiuzhe Wu, Wang Wang, Bo Zhao, Zeke Xie, Gui-Song Xia, Xiaojuan Qi
https://arxiv.org/abs/2508.14648

Understanding Data Influence with Differential Approximation
Data plays a pivotal role in the groundbreaking advancements in artificial intelligence. The quantitative analysis of data significantly contributes to model training, enhancing both the efficiency and quality of data utilization. However, existing data analysis tools often lag in accuracy. For instance, many of these tools even assume that the loss function of neural networks is convex. These limitations make it challenging to implement current methods effectively. In this paper, we introduce …

Non-radial solutions for the critical quasi-linear H\'{e}non equation involving $p$-Laplacian in $\R^N$
Wei Dai, Lixiu Duan, Changfeng Gui, Yuan Li
https://arxiv.org/abs/2508.13539

Non-radial solutions for the critical quasi-linear Hénon equation involving $p$-Laplacian in $\R^N$
In this paper, we investigate the following $D^{1,p}$-critical quasi-linear Hénon equation involving $p$-Laplacian \begin{equation*}\label{00} \left\{ \begin{aligned} &-Δ_p u=|x|^αu^{p_\al^*-1}, & x\in \R^N, \\ &u>0, & x\in \R^N, \end{aligned} \right. \end{equation*} where $N\geq2$, $10$. By carefully studying the linearized problem and applying the approximation method and bifurcation theory, we prove that, when the parameter $\al$ ta…

ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents
Hanyu Lai, Xiao Liu, Yanxiao Zhao, Han Xu, Hanchen Zhang, Bohao Jing, Yanyu Ren, Shuntian Yao, Yuxiao Dong, Jie Tang
https://arxiv.org/abs/2508.14040

ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents
We introduce ComputerRL, a framework for autonomous desktop intelligence that enables agents to operate complex digital workspaces skillfully. ComputerRL features the API-GUI paradigm, which unifies programmatic API calls and direct GUI interaction to address the inherent mismatch between machine agents and human-centric desktop environments. Scaling end-to-end RL training is crucial for improvement and generalization across diverse desktop tasks, yet remains challenging due to environmental in…

Contact Term Algebras and Dijkgraaf's Master Equation
Zhengping Gui, Si Li, Xinxing Tang
https://arxiv.org/abs/2506.13194 https://

Contact Term Algebras and Dijkgraaf's Master Equation
This paper is devoted to study integrable deformations of chiral conformal field theories on elliptic curves from the viewpoint of contact algebra. We introduce the relevant integrable condition within the framework of conformal vertex algebra, and derive the contact term relations among certain local operators. We investigate three versions of genus one partition functions and derive the contact equations. This leads to a rigorous formulation of Dijkgraaf's master equation \cite{Dijk1996master…

»How to build a copy-to-clipboard HTML«
– by @…
With JavaScript set HTML to easy use web GUI's.
📃 https://gomakethings.com/how-…

How to build a copy-to-clipboard HTML Web Component
Yesterday, we looked at how to copy items to a user’s clipboard with JavaScriprt. Today, we’re going to turn that into an HTML Web Component. Let’s dig in! The Custom Element For this Web Component, let’s use a element. With the HTML Web Component approach, we start with HTML and enhance it rather than rendering all the things with JavaScript. Let’s add a with our desired text inside the custom element.

This https://arxiv.org/abs/2504.13865 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

A Survey on (M)LLM-Based GUI Agents
Graphical User Interface (GUI) Agents have emerged as a transformative paradigm in human-computer interaction, evolving from rule-based automation scripts to sophisticated AI-driven systems capable of understanding and executing complex interface operations. This survey provides a comprehensive examination of the rapidly advancing field of LLM-based GUI Agents, systematically analyzing their architectural foundations, technical components, and evaluation methodologies. We identify and analyze f…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/3]:
- MemGuide: Intent-Driven Memory Selection for Goal-Oriented Multi-Session LLM Agents
Du, Wang, He, Liang, Wang, Li, Gui, Pan, Xu, Wong

GUIPilot: A Consistency-based Mobile GUI Testing Approach for Detecting Application-specific Bugs
Ruofan Liu, Xiwen Teoh, Yun Lin, Guanjie Chen, Ruofei Ren, Denys Poshyvanyk, Jin Song Dong
https://arxiv.org/abs/2506.07385

GUIPilot: A Consistency-based Mobile GUI Testing Approach for Detecting Application-specific Bugs
In this work, we propose GUIPilot, an approach for detecting inconsistencies between the mobile design and their implementations. The mobile design usually consists of design mock-ups that specify (1) the expected screen appearances (e.g., widget layouts, colors, and shapes) and (2) the expected screen behaviors, regarding how one screen can transition into another (e.g., labeled widgets with textual description). Given a design mock-up and the implementation of its application, GUIPilot report…

Repurposing an old fileserver as another backup server using #TrueNAS… First, I want to pull out any disks with reallocated sectors. Most disks are more than 5 years old and my plan is to replace future failing HDDs with larger ones. As an appliance, TrueNAS is not meant for low-level tinkering. The GUI only shows actual uncorrected sectors as SMART errors and has no way to light up a disk slot o…

Evidence of scaling advantage on an NP-Complete problem with enhanced quantum solvers
Quanfeng Lu, Shijie Wei, Keren Li, Pan Gao, Bao Yan, Muxi Zheng, Haoran Zhang, Jinfeng Zeng, Gui-Lu Long
https://arxiv.org/abs/2508.08869

Evidence of scaling advantage on an NP-Complete problem with enhanced quantum solvers
Achieving quantum advantage remains a key milestone in the noisy intermediate-scale quantum era. Without rigorous complexity proofs, scaling advantage-where quantum resource requirements grow more slowly than their classical counterparts-serves as the primary indicator. However, direct applications of quantum optimization algorithms to classically intractable problems have yet to demonstrate this advantage. To address this challenge, we develop enhanced quantum solvers for the NP-complete one-i…

Backdooring Self-Supervised Contrastive Learning by Noisy Alignment
Tuo Chen, Jie Gui, Minjing Dong, Ju Jia, Lanting Fang, Jian Liu
https://arxiv.org/abs/2508.14015 https://

Backdooring Self-Supervised Contrastive Learning by Noisy Alignment
Self-supervised contrastive learning (CL) effectively learns transferable representations from unlabeled data containing images or image-text pairs but suffers vulnerability to data poisoning backdoor attacks (DPCLs). An adversary can inject poisoned images into pretraining datasets, causing compromised CL encoders to exhibit targeted misbehavior in downstream tasks. Existing DPCLs, however, achieve limited efficacy due to their dependence on fragile implicit co-occurrence between backdoor and …

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning
Yao Lu, Hongyu Gao, Zhuangzhi Chen, Dongwei Xu, Yun Lin, Qi Xuan, Guan Gui
https://arxiv.org/abs/2507.12011

DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning
Although deep neural networks have made remarkable achievements in the field of automatic modulation recognition (AMR), these models often require a large amount of labeled data for training. However, in many practical scenarios, the available target domain data is scarce and difficult to meet the needs of model training. The most direct way is to collect data manually and perform expert annotation, but the high time and labor costs are unbearable. Another common method is data augmentation. Al…

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[2/3]:
- UniCalib: Targetless LiDAR-Camera Calibration via Probabilistic Flow on Unified Depth Representat...
Shu Han, Xubo Zhu, Ji Wu, Ximeng Cai, Wen Yang, Huai Yu, Gui-Song Xia

Least total curvature solutions to steady Euler system and monotone solutions to semilinear equations in a strip
Changfeng Gui, David Ruiz, Chunjing Xie, Huan Xu
https://arxiv.org/abs/2507.11837

Least total curvature solutions to steady Euler system and monotone solutions to semilinear equations in a strip
This paper focuses on establishing the existence of a class of steady solutions, termed least total curvature solutions, to the incompressible Euler system in a strip. The solutions obtained in this paper complement the least total curvature solutions already known. Our approach employs a minimization procedure to identify a monotone heteroclinic solution for a conveniently chosen semilinear elliptic PDE. This method also enables us to construct positive and monotone (and consequently stable) s…

This https://arxiv.org/abs/2407.17490 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

AMEX: Android Multi-annotation Expo Dataset for Mobile GUI Agents
AI agents have drawn increasing attention mostly on their ability to perceive environments, understand tasks, and autonomously achieve goals. To advance research on AI agents in mobile scenarios, we introduce the Android Multi-annotation EXpo (AMEX), a comprehensive, large-scale dataset designed for generalist mobile GUI-control agents which are capable of completing tasks by directly interacting with the graphical user interface (GUI) on mobile devices. AMEX comprises over 104K high-resolution…

Phi-Ground Tech Report: Advancing Perception in GUI Grounding
Miaosen Zhang, Ziqiang Xu, Jialiang Zhu, Qi Dai, Kai Qiu, Yifan Yang, Chong Luo, Tianyi Chen, Justin Wagle, Tim Franklin, Baining Guo
https://arxiv.org/abs/2507.23779

Phi-Ground Tech Report: Advancing Perception in GUI Grounding
With the development of multimodal reasoning models, Computer Use Agents (CUAs), akin to Jarvis from \textit{"Iron Man"}, are becoming a reality. GUI grounding is a core component for CUAs to execute actual actions, similar to mechanical control in robotics, and it directly leads to the success or failure of the system. It determines actions such as clicking and typing, as well as related parameters like the coordinates for clicks. Current end-to-end grounding models still achieve less than 65\…

InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
Yuhang Liu, Zeyu Liu, Shuanghe Zhu, Pengxiang Li, Congkai Xie, Jiasheng Wang, Xueyu Hu, Xiaotian Han, Jianbo Yuan, Xinyao Wang, Shengyu Zhang, Hongxia Yang, Fei Wu
https://arxiv.org/abs/2508.05731

InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
The emergence of Multimodal Large Language Models (MLLMs) has propelled the development of autonomous agents that operate on Graphical User Interfaces (GUIs) using pure visual input. A fundamental challenge is robustly grounding natural language instructions. This requires a precise spatial alignment, which accurately locates the coordinates of each element, and, more critically, a correct semantic alignment, which matches the instructions to the functionally appropriate UI element. Although Re…

Observation and Modulation of the Quantum Mpemba Effect on a Superconducting Quantum Processor
Yueshan Xu, Cai-Ping Fang, Bing-Jie Chen, Ming-Chuan Wang, Zi-Yong Ge, Yun-Hao Shi, Yu Liu, Cheng-Lin Deng, Kui Zhao, Zheng-He Liu, Tian-Ming Li, Hao Li, Ziting Wang, Gui-Han Liang, Da'er Feng, Xueyi Guo, Xu-Yang Gu, Yang He, Hao-Tian Liu, Zheng-Yang Mei, Yongxi Xiao, Yu Yan, Yi-Han Yu, Wei-Ping Yuan, Jia-Chi Zhang, Zheng-An Wang, Gangqin Liu, Xiaohui Song, Ye Tian, Yu-Ran Zhang, Shi-Xin …

Observation and Modulation of the Quantum Mpemba Effect on a Superconducting Quantum Processor
In non-equilibrium quantum many-body systems, the quantum Mpemba effect (QME) emerges as a counterintuitive phenomenon: systems exhibiting greater initial symmetry breaking restore symmetry faster than those with less. While theoretical exploration of QME has surged, experimental studies on its multidimensional modulation remain limited. Here, we report the observation and control of QME using a superconducting processor featuring a unique fully connected, tunable-coupling architecture that ena…

Pre-Trained Policy Discriminators are General Reward Models
Shihan Dou, Shichun Liu, Yuming Yang, Yicheng Zou, Yunhua Zhou, Shuhao Xing, Chenhao Huang, Qiming Ge, Demin Song, Haijun Lv, Songyang Gao, Chengqi Lv, Enyu Zhou, Honglin Guo, Zhiheng Xi, Wenwei Zhang, Qipeng Guo, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Tao Gui, Kai Chen
https://

Integrating Diffusion-based Multi-task Learning with Online Reinforcement Learning for Robust Quadruped Robot Control
Xinyao Qin, Xiaoteng Ma, Yang Qi, Qihan Liu, Chuanyi Xue, Ning Gui, Qinyu Dong, Jun Yang, Bin Liang
https://arxiv.org/abs/2507.05674

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
Shurui Gui, Shuiwang Ji
https://arxiv.org/abs/2506.09433 https://

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
While large language models (LLMs) have demonstrated remarkable capabilities in language modeling, recent studies reveal that they often fail on out-of-distribution (OOD) samples due to spurious correlations acquired during pre-training. Here, we aim to mitigate such spurious correlations through causality-aware post-training (CAPT). By decomposing a biased prediction into two unbiased steps, known as \textit{event estimation} and \textit{event intervention}, we reduce LLMs' pre-training biases…

TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices
Wataru Kawabe, Hiroto Fukuda, Akihisa Shitara, Yuri Nakao, Yusuke Sugano
https://arxiv.org/abs/2508.00252

TofuML: A Spatio-Physical Interactive Machine Learning Device for Interactive Exploration of Machine Learning for Novices
We introduce TofuML, an interactive system designed to make machine learning (ML) concepts more accessible and engaging for non-expert users. Unlike conventional GUI-based systems, TofuML employs a physical and spatial interface consisting of a small device and a paper mat, allowing users to train and evaluate sound classification models through intuitive, toy-like interactions. Through two user studies -- a comparative study against a GUI-based version and a public event deployment -- we inves…

Flexible Readout and Unconditional Reset for Superconducting Multi-Qubit Processors with Tunable Purcell Filters
Yong-Xi Xiao, Da'er Feng, Xu-Yang Gu, Gui-Han Liang, Ming-Chuan Wang, Zheng-Yu Peng, Bing-Jie Chen, Yu Yan, Zheng-Yang Mei, Si-Lu Zhao, Yi-Zhou Bu, Cheng-Lin Deng, Xiaohui Song, Dongning Zheng, Yu-Xiang Zhang, Yun-Hao Shi, Zhongcheng Xiang, Kai Xu, Heng Fan

Flexible Readout and Unconditional Reset for Superconducting Multi-Qubit Processors with Tunable Purcell Filters
Qubit readout and reset are critical components for the practical realization of quantum computing systems, as outlined by the DiVincenzo criteria. Here, we present a scalable architecture employing frequency-tunable nonlinear Purcell filters designed specifically for superconducting qubits. This architecture enables flexible readout and unconditional reset functionalities. Our readout protocol dynamically adjusts the effective linewidth of the readout resonator through a tunable filter, optimi…

VasoMIM: Vascular Anatomy-Aware Masked Image Modeling for Vessel Segmentation
De-Xing Huang, Xiao-Hu Zhou, Mei-Jiang Gui, Xiao-Liang Xie, Shi-Qi Liu, Shuang-Yi Wang, Tian-Yu Xiang, Rui-Ze Ma, Nu-Fang Xiao, Zeng-Guang Hou
https://arxiv.org/abs/2508.10794

VasoMIM: Vascular Anatomy-Aware Masked Image Modeling for Vessel Segmentation
Accurate vessel segmentation in X-ray angiograms is crucial for numerous clinical applications. However, the scarcity of annotated data presents a significant challenge, which has driven the adoption of self-supervised learning (SSL) methods such as masked image modeling (MIM) to leverage large-scale unlabeled data for learning transferable representations. Unfortunately, conventional MIM often fails to capture vascular anatomy because of the severe class imbalance between vessel and background…

AutoGEEval : A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Shuyang Hou, Zhangxiao Shen, Huayi Wu, Haoyue Jiao, Ziqi Liu, Lutong Xie, Chang Liu, Jianyuan Liang, Yaxian Qing, Xiaopu Zhang, Dehua Peng, Zhipeng Gui, Xuefeng Guan
https://

AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task remain absent. This study presents AutoGEEval++, an enhanced framework building on AutoGEEval, and the first automated assessment system for large language models (LLMs) generating geospatial code on Google Earth Engine (GEE). It supports diverse data modalities and varying task complexities. Built on the GEE Python …

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[2/2]:
- GUI-G$^2$: Gaussian Reward Modeling for GUI Grounding
Tang, Gu, Lu, Liu, Shen, Meng, Wang, Zhang, Shen, Lu, Xiao, Zhuang

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/6]:
- NatureGAIA: Pushing the Frontiers of GUI Agents with a Challenging Benchmark and High-Quality Tra...
Zihan Zheng, Tianle Cui, Chuwen Xie, Jiahui Zhang, Jiahui Pan, Lewei He, Qianglong Chen

SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models
Pingchuan Ma, Xiaopei Yang, Yusong Li, Ming Gui, Felix Krause, Johannes Schusterbauer, Bj\"orn Ommer
https://arxiv.org/abs/2508.03402

SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models
Explicitly disentangling style and content in vision models remains challenging due to their semantic overlap and the subjectivity of human perception. Existing methods propose separation through generative or discriminative objectives, but they still face the inherent ambiguity of disentangling intertwined concepts. Instead, we ask: Can we bypass explicit disentanglement by learning to merge style and content invertibly, allowing separation to emerge naturally? We propose SCFlow, a flow-matchi…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[4/6]:
- SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers
Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, Lin Gui, Yulan He