Tootfinder

Auto-scaling Continuous Memory for GUI Agent
Wenyi Wu, Kun Zhou, Ruoxin Yuan, Vivian Yu, Stephen Wang, Zhiting Hu, Biwei Huang
https://arxiv.org/abs/2510.09038 https://

Auto-scaling Continuous Memory for GUI Agent
We study how to endow GUI agents with scalable memory that help generalize across unfamiliar interfaces and long-horizon tasks. Prior GUI agents compress past trajectories into text tokens, which balloons context length and misses decisive visual cues (e.g., exact widget size and position). We propose a continuous memory that encodes each GUI trajectory into a fixed-length sequence of continuous embeddings using the VLM itself as an encoder; these embeddings are plugged directly into the backbo…

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…

#HomeAssistant is pretty good.
It has some quirks, but it's not as much hassle as I feared. I had to edit 4 lines of YAML, but everything else I wanted was in the GUI.
Finally, switch to the #Matter standard paid off. I can keep devices shared with HomeKit, while having way bet…

🇺🇦 #NowPlaying on #BBC6Music
High Vis:
🎵 Guided Tour
#HighVis
https://highvis.bandcamp.com/track/guided-tour
https://open.spotify.com/track/0afflx9Jk8wIFitFncBnyS

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/5]:
- Auto-scaling Continuous Memory for GUI Agent
Wenyi Wu, Kun Zhou, Ruoxin Yuan, Vivian Yu, Stephen Wang, Zhiting Hu, Biwei Huang

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

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…

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…

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…

An Open-Source Simulation and Data Management Tool for EnergyPlus Building Models
Ninad Gaikwad, Kasey Dettlaff, Athul Jose P, Anamika Dubey
https://arxiv.org/abs/2508.09130 htt…

An Open-Source Simulation and Data Management Tool for EnergyPlus Building Models
We present a new open-source, GUI-based application created using Plotly-Dash, along with an integrated PostgreSQL-based relational database, developed to streamline EnergyPlus building model simulation workflows. The application facilitates data generation, aggregation (across thermal zones), and visualization based on customizable user preferences, while the database efficiently stores and retrieves complex simulation data generated by EnergyPlus. We demonstrate the need for this application …

On the existence of self-similar solutions to the steady Navier-Stokes equations in high dimensions
Jeaheang Bang, Changfeng Gui, Hao Liu, Yun Wang, Chunjing Xie
https://arxiv.org/abs/2510.10488

On the existence of self-similar solutions to the steady Navier-Stokes equations in high dimensions
We prove that the steady incompressible Navier-Stokes equations with any given $(-3)$-homogeneous, locally Lipschitz external force on $\mathbb{R}^n\setminus\{0\}$, $4\leq n\leq 16$, have at least one $(-1)$-homogeneous solution which is scale-invariant and regular away from the origin. The global uniqueness of the self-similar solution is obtained as long as the external force is small. The key observation is to exploit a nice relation between the radial component of the velocity and the total…

Breaking the Sabatier Principle by Dynamic Adsorption-Desorption Decoupling in Electrocatalytic Hydrogen Evolution
Zi-Xuan Yang, Lei Li, Tao Huang, Hui Wan, X. S. Wang, Gui-Fang Huang, Wangyu Hu, Wei-Qing Huang
https://arxiv.org/abs/2510.10555

Breaking the Sabatier Principle by Dynamic Adsorption-Desorption Decoupling in Electrocatalytic Hydrogen Evolution
The Sabatier principle establishes a fundamental trade-off in heterogeneous electrocatalysis.In the hydrogen evolution reaction (HER), this trade-off is manifested by the coupling of Volmer step, which requires strong hydrogen adsorption, with the Heyrovsky/Tafel step, which favors facile desorption, thus giving rise to the classical volcano relationship and limiting activity even at $ΔG=0$. Here, we demonstrate a ferroelectric platform with dynamic tunability -- monolayer GeS$_2$ decorated wi…

ReInAgent: A Context-Aware GUI Agent Enabling Human-in-the-Loop Mobile Task Navigation
Haitao Jia, Ming He, Zimo Yin, Likang Wu, Jianping Fan, Jitao Sang
https://arxiv.org/abs/2510.07988

ReInAgent: A Context-Aware GUI Agent Enabling Human-in-the-Loop Mobile Task Navigation
Mobile GUI agents exhibit substantial potential to facilitate and automate the execution of user tasks on mobile phones. However, exist mobile GUI agents predominantly privilege autonomous operation and neglect the necessity of active user engagement during task execution. This omission undermines their adaptability to information dilemmas including ambiguous, dynamically evolving, and conflicting task scenarios, leading to execution outcomes that deviate from genuine user requirements and pref…

Trion FPGA adventure update:
It looks like you need to import the generated .isf into the interface designer if you want to switch between RTL and GUI flows (e.g. to use the GUI to constrain I/O blocks that were inferred from RTL). This is a pain, but at least it's something I can work around now that I understand it.
Next problem: I think I've found my first datasheet errata. The EFX_DDIO documentation in the Quantium Trion Primitives User Guide lists DDIO, DDIO_RESYNC, …

Dexplore: Scalable Neural Control for Dexterous Manipulation from Reference-Scoped Exploration
Sirui Xu, Yu-Wei Chao, Liuyu Bian, Arsalan Mousavian, Yu-Xiong Wang, Liang-Yan Gui, Wei Yang
https://arxiv.org/abs/2509.09671

Dexplore: Scalable Neural Control for Dexterous Manipulation from Reference-Scoped Exploration
Hand-object motion-capture (MoCap) repositories offer large-scale, contact-rich demonstrations and hold promise for scaling dexterous robotic manipulation. Yet demonstration inaccuracies and embodiment gaps between human and robot hands limit the straightforward use of these data. Existing methods adopt a three-stage workflow, including retargeting, tracking, and residual correction, which often leaves demonstrations underused and compound errors across stages. We introduce Dexplore, a unified …

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…

VeriOS: Query-Driven Proactive Human-Agent-GUI Interaction for Trustworthy OS Agents
Zheng Wu, Heyuan Huang, Xingyu Lou, Xiangmou Qu, Pengzhou Cheng, Zongru Wu, Weiwen Liu, Weinan Zhang, Jun Wang, Zhaoxiang Wang, Zhuosheng Zhang
https://arxiv.org/abs/2509.07553

VeriOS: Query-Driven Proactive Human-Agent-GUI Interaction for Trustworthy OS Agents
With the rapid progress of multimodal large language models, operating system (OS) agents become increasingly capable of automating tasks through on-device graphical user interfaces (GUIs). However, most existing OS agents are designed for idealized settings, whereas real-world environments often present untrustworthy conditions. To mitigate risks of over-execution in such scenarios, we propose a query-driven human-agent-GUI interaction framework that enables OS agents to decide when to query h…

A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants
Hans G. W. van Dam
https://arxiv.org/abs/2510.06223 https://arxiv.or…

A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants
Advances in large language models (LLMs) and real-time speech recognition now make it possible to issue any graphical user interface (GUI) action through natural language and receive the corresponding system response directly through the GUI. Most production applications were never designed with speech in mind. This article provides a concrete architecture that enables GUIs to interface with LLM-based speech-enabled assistants. The architecture makes an application's navigation graph and sema…

APEX: Automatic Event Sequence Generation for Android Applications
Wenhao Chen, Morris Chang, Witawas Srisa-an, Yong Guan
https://arxiv.org/abs/2509.02412 https://

APEX: Automatic Event Sequence Generation for Android Applications
Due to the event driven nature and the versatility of GUI designs in Android programs, it is challenging to generate event sequences with adequate code coverage within a reasonable time. A common approach to handle this issue is to rely on GUI models to generate event sequences. These sequences can be effective in covering GUI states, but inconsistent in exposing program behaviors that require specific inputs. A major obstacle to generate such specific inputs is the lack of a systematic GUI exp…

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…

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…

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,

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…

Was able to grab and install Lagrange (for accessing Gopher/Gemini sites) here on my laptop that has Mint on it, just by searching for Lagrange in the Software Manager (gotta love Linux). Installed, launched-- and yeah, it really is a great, clean GUI. Also, you can see my Rogue desktop background 😂
#Gemini #Gopher …

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…

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

Validity and Power of Heavy-Tailed Combination Tests under Asymptotic Dependence
Lin Gui, Tiantian Mao, Jingshu Wang, Ruodu Wang
https://arxiv.org/abs/2508.05818 https://…

Validity and Power of Heavy-Tailed Combination Tests under Asymptotic Dependence
Heavy-tailed combination tests, such as the Cauchy combination test and harmonic mean p-value method, are widely used for testing global null hypotheses by aggregating dependent p-values. However, their theoretical guarantees under general dependence structures remain limited. We develop a unified framework using multivariate regularly varying copulas to model the joint behavior of p-values near zero. Within this framework, we show that combination tests remain asymptotically valid when the tra…

Crosslisted article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
Yunbo Li, Jiaping Gui, Zhihang Deng, Fanchao Meng, Yue Wu

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…

Hab mir nun einen zweiten AP gekauft der nur via VPN ins Internet darf. Das GL-inet Gerät ist klein, aber die Leistung beeindruckt. Hat eine sehr gute GUI und darunter läuft ein OpenWRT. AdGuard z.b. kannst du einfach per klick installieren, VPN Einrichtung geht ebenfalls super einfach.
https://amzn.eu/d/3hj3EAC…

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning
Zhiheng Xi, Jixuan Huang, Chenyang Liao, Baodai Huang, Honglin Guo, Jiaqi Liu, Rui Zheng, Junjie Ye, Jiazheng Zhang, Wenxiang Chen, Wei He, Yiwen Ding, Guanyu Li, Zehui Chen, Zhengyin Du, Xuesong Yao, Yufei Xu, Jiecao Chen, Tao Gui, Zuxuan Wu, Qi Zhang, Xuanjing Huang, Yu-Gang Jiang

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning
Developing autonomous LLM agents capable of making a series of intelligent decisions to solve complex, real-world tasks is a fast-evolving frontier. Like human cognitive development, agents are expected to acquire knowledge and skills through exploration and interaction with the environment. Despite advances, the community still lacks a unified, interactive reinforcement learning (RL) framework that can effectively train such agents from scratch -- without relying on supervised fine-tuning (SFT…

KG-RAG: Enhancing GUI Agent Decision-Making via Knowledge Graph-Driven Retrieval-Augmented Generation
Ziyi Guan, Jason Chun Lok Li, Zhijian Hou, Pingping Zhang, Donglai Xu, Yuzhi Zhao, Mengyang Wu, Jinpeng Chen, Thanh-Toan Nguyen, Pengfei Xian, Wenao Ma, Shengchao Qin, Graziano Chesi, Ngai Wong
https://arxiv.org/abs/2509.00366

KG-RAG: Enhancing GUI Agent Decision-Making via Knowledge Graph-Driven Retrieval-Augmented Generation
Despite recent progress, Graphic User Interface (GUI) agents powered by Large Language Models (LLMs) struggle with complex mobile tasks due to limited app-specific knowledge. While UI Transition Graphs (UTGs) offer structured navigation representations, they are underutilized due to poor extraction and inefficient integration. We introduce KG-RAG, a Knowledge Graph-driven Retrieval-Augmented Generation framework that transforms fragmented UTGs into structured vector databases for efficient real…

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness
Kung-Hsiang Huang, Haoyi Qiu, Yutong Dai, Caiming Xiong, Chien-Sheng Wu
https://arxiv.org/abs/2510.00536

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness
Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. However, they also face the inefficiency challenge as they process long sequences of high-resolution screenshots and solving long-horizon tasks, making inference slow, costly and memory-bound. While key-value (KV) caching can mitigate this, storing the full cache is prohibitive for image-heavy contexts. Existing cache-compression methods are sub-optima…

Numerical analysis of the homogeneous Landau equation: approximation, error estimates and simulation
Francis Filbet (IMT), Yanzhi Gui (THU), Ling-Bing He (THU)
https://arxiv.org/abs/2509.09276

Numerical analysis of the homogeneous Landau equation: approximation, error estimates and simulation
We construct a numerical solution to the spatially homogeneous Landau equation with Coulomb potential on a domain $D_L$ with N retained Fourier modes. By deriving an explicit error estimate in terms of $L$ and $N$, we demonstrate that for any prescribed error tolerance and fixed time interval $[0, T ]$, there exist choices of $D_L$ and $N$ satisfying explicit conditions such that the error between the numerical and exact solutions is below the tolerance. Specifically, the estimate shows that su…

Texture-zeros in minimal seesaw from non-invertible symmetry fusion rules
Zheng Jiang, Bu-Yao Qu, Gui-Jun Ding
https://arxiv.org/abs/2510.07236 https://arx…

Texture-zeros in minimal seesaw from non-invertible symmetry fusion rules
The $Z_2$ gauging of $Z_N$ symmetry can enforce certain elements of the fermion Yukawa couplings to vanish. We have performed a systematical study of texture zero patterns of lepton mass matrices in the minimal seesaw model, and we present all the possible patterns of the charged lepton Yukawa coupling $Y_E$, neutrino Yukawa coupling $Y_ν$, right-handed neutrino mass matrix $M_R$ and the light neutrino mass matrix $M_ν$ which can be derived from the $Z_2$ gauging of $Z_N$ symmetry. The realiz…

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/

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…

About a month ago I was a bit too optimistic*, the admin took over a month to complete....: Only last Tuesday Reasonable Sourcery was officially inCOOPerated.
Today we finally sent out the official introduction:
<https://lists.gnu.org/archive/html/guix-devel/2025…

Replaced article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
[1/1]:
- Large Language Models for Mobile GUI Text Input Generation: An Empirical Study
Chenhui Cui, Tao Li, Junjie Wang, Chunyang Chen, Dave Towey, Rubing Huang

PG-Agent: An Agent Powered by Page Graph
Weizhi Chen, Ziwei Wang, Leyang Yang, Sheng Zhou, Xiaoxuan Tang, Jiajun Bu, Yong Li, Wei Jiang
https://arxiv.org/abs/2509.03536 https://…

PG-Agent: An Agent Powered by Page Graph
Graphical User Interface (GUI) agents possess significant commercial and social value, and GUI agents powered by advanced multimodal large language models (MLLMs) have demonstrated remarkable potential. Currently, existing GUI agents usually utilize sequential episodes of multi-step operations across pages as the prior GUI knowledge, which fails to capture the complex transition relationship between pages, making it challenging for the agents to deeply perceive the GUI environment and generaliz…

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

Multi-modal Uncertainty Robust Tree Cover Segmentation For High-Resolution Remote Sensing Images
Yuanyuan Gui, Wei Li, Yinjian Wang, Xiang-Gen Xia, Mauro Marty, Christian Ginzler, Zuyuan Wang
https://arxiv.org/abs/2509.04870

Multi-modal Uncertainty Robust Tree Cover Segmentation For High-Resolution Remote Sensing Images
Recent advances in semantic segmentation of multi-modal remote sensing images have significantly improved the accuracy of tree cover mapping, supporting applications in urban planning, forest monitoring, and ecological assessment. Integrating data from multiple modalities-such as optical imagery, light detection and ranging (LiDAR), and synthetic aperture radar (SAR)-has shown superior performance over single-modality methods. However, these data are often acquired days or even months apart, du…

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,

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.

InterAct: Advancing Large-Scale Versatile 3D Human-Object Interaction Generation
Sirui Xu, Dongting Li, Yucheng Zhang, Xiyan Xu, Qi Long, Ziyin Wang, Yunzhi Lu, Shuchang Dong, Hezi Jiang, Akshat Gupta, Yu-Xiong Wang, Liang-Yan Gui
https://arxiv.org/abs/2509.09555

InterAct: Advancing Large-Scale Versatile 3D Human-Object Interaction Generation
While large-scale human motion capture datasets have advanced human motion generation, modeling and generating dynamic 3D human-object interactions (HOIs) remain challenging due to dataset limitations. Existing datasets often lack extensive, high-quality motion and annotation and exhibit artifacts such as contact penetration, floating, and incorrect hand motions. To address these issues, we introduce InterAct, a large-scale 3D HOI benchmark featuring dataset and methodological advancements. Fir…

I will be talking at the next #DevOps #Prague meetup. You should join. It's free to attend and requires registration.
https://www.

October DevOps Meetup, Thu, Oct 23, 2025, 6:00 PM | Meetup
Talk 0 **Goodbye, DB Passwords: Vibe-Coding a Rust GUI for CloudSQL Auth Proxy** by Petr Macháček DevOps Engineer from Rohlik If you're still juggling database passwords a

🇺🇦 #NowPlaying on #BBC6Music's #AmyLamé
High Vis:
🎵 Guided Tour
#HighVis
https://highvis.bandcamp.com/track/guided-tour
https://open.spotify.com/track/0afflx9Jk8wIFitFncBnyS

SparkUI-Parser: Enhancing GUI Perception with Robust Grounding and Parsing
Hongyi Jing, Jiafu Chen, Chen Rao, Ziqiang Dang, Jiajie Teng, Tianyi Chu, Juncheng Mo, Shuo Fang, Huaizhong Lin, Rui Lv, Chenguang Ma, Lei Zhao
https://arxiv.org/abs/2509.04908

SparkUI-Parser: Enhancing GUI Perception with Robust Grounding and Parsing
The existing Multimodal Large Language Models (MLLMs) for GUI perception have made great progress. However, the following challenges still exist in prior methods: 1) They model discrete coordinates based on text autoregressive mechanism, which results in lower grounding accuracy and slower inference speed. 2) They can only locate predefined sets of elements and are not capable of parsing the entire interface, which hampers the broad application and support for downstream tasks. To address the a…

TriQuest:An AI Copilot-Powered Platform for Interdisciplinary Curriculum Design
Huazhen Wang, Huimin Yang, Hainbin Lin, Yan Dong, Lili Chen, Liangliang Xia, Wenwen Xu
https://arxiv.org/abs/2510.03369

TriQuest:An AI Copilot-Powered Platform for Interdisciplinary Curriculum Design
Interdisciplinary teaching is a cornerstone of modern curriculum reform, but its implementation is hindered by challenges in knowledge integration and time-consuming lesson planning. Existing tools often lack the required pedagogical and domain-specific depth.We introduce TriQuest, an AI-copilot platform designed to solve these problems. TriQuest uses large language models and knowledge graphs via an intuitive GUI to help teachers efficiently generate high-quality interdisciplinary lesson plans…

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 …

AgenticRAG: Tool-Augmented Foundation Models for Zero-Shot Explainable Recommender Systems
Bo Ma, Hang Li, ZeHua Hu, XiaoFan Gui, LuYao Liu, Simon Liu
https://arxiv.org/abs/2510.02668

AgenticRAG: Tool-Augmented Foundation Models for Zero-Shot Explainable Recommender Systems
Foundation models have revolutionized artificial intelligence, yet their application in recommender systems remains limited by reasoning opacity and knowledge constraints. This paper introduces AgenticRAG, a novel framework that combines tool-augmented foundation models with retrieval-augmented generation for zero-shot explainable recommendations. Our approach integrates external tool invocation, knowledge retrieval, and chain-of-thought reasoning to create autonomous recommendation agents capa…

🇺🇦 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

#Accessibility modelers using #r5r #rstats, check this GUI for playing around with R5 network. If many people find it useful, I would get signal if I should invest any more free time into it.

Improving GUI Grounding with Explicit Position-to-Coordinate Mapping
Suyuchen Wang, Tianyu Zhang, Ahmed Masry, Christopher Pal, Spandana Gella, Bang Liu, Perouz Taslakian
https://arxiv.org/abs/2510.03230

Improving GUI Grounding with Explicit Position-to-Coordinate Mapping
GUI grounding, the task of mapping natural-language instructions to pixel coordinates, is crucial for autonomous agents, yet remains difficult for current VLMs. The core bottleneck is reliable patch-to-pixel mapping, which breaks when extrapolating to high-resolution displays unseen during training. Current approaches generate coordinates as text tokens directly from visual features, forcing the model to infer complex position-to-pixel mappings implicitly; as a result, accuracy degrades and fai…

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.

UItron: Foundational GUI Agent with Advanced Perception and Planning
Zhixiong Zeng, Jing Huang, Liming Zheng, Wenkang Han, Yufeng Zhong, Lei Chen, Longrong Yang, Yingjie Chu, Yuzhi He, Lin Ma
https://arxiv.org/abs/2508.21767

UItron: Foundational GUI Agent with Advanced Perception and Planning
GUI agent aims to enable automated operations on Mobile/PC devices, which is an important task toward achieving artificial general intelligence. The rapid advancement of VLMs accelerates the development of GUI agents, owing to their powerful capabilities in visual understanding and task planning. However, building a GUI agent remains a challenging task due to the scarcity of operation trajectories, the availability of interactive infrastructure, and the limitation of initial capabilities in fou…

IndusGCC: A Data Benchmark and Evaluation Framework for GUI-Based General Computer Control in Industrial Automation
Xiaoran Yang, Yuyang Du, Kexin Chen, Soung Chang Liew, Jiamin Lu, Ziyu Guo, Xiaoyan Liu, Qun Yang, Shiqi Xu, Xingyu Fan, Yuchen Pan, Taoyong Cui, Hongyu Deng, Boris Dudder, Jianzhang Pan, Qun Fang, Pheng Ann Heng
https://arxi…

IndusGCC: A Data Benchmark and Evaluation Framework for GUI-Based General Computer Control in Industrial Automation
As Industry 4.0 progresses, flexible manufacturing has become a cornerstone of modern industrial systems, with equipment automation playing a pivotal role. However, existing control software for industrial equipment, typically reliant on graphical user interfaces (GUIs) that require human interactions such as mouse clicks or screen touches, poses significant barriers to the adoption of code-based equipment automation. Recently, Large Language Model-based General Computer Control (LLM-GCC) has e…

Evaluating LLM-Generated Legal Explanations for Regulatory Compliance in Social Media Influencer Marketing
Haoyang Gui, Thales Bertaglia, Taylor Annabell, Catalina Goanta, Tjomme Dooper, Gerasimos Spanakis
https://arxiv.org/abs/2510.08111

Evaluating LLM-Generated Legal Explanations for Regulatory Compliance in Social Media Influencer Marketing
The rise of influencer marketing has blurred boundaries between organic content and sponsored content, making the enforcement of legal rules relating to transparency challenging. Effective regulation requires applying legal knowledge with a clear purpose and reason, yet current detection methods of undisclosed sponsored content generally lack legal grounding or operate as opaque "black boxes". Using 1,143 Instagram posts, we compare gpt-5-nano and gemini-2.5-flash-lite under three prompting str…

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Haoming Wang, Haoyang Zou, Huatong Song, Jiazhan Feng, Junjie Fang, Junting Lu, Longxiang Liu, Qinyu Luo, Shihao Liang, Shijue Huang, Wanjun Zhong, Yining Ye, Yujia Qin, Yuwen Xiong, Yuxin Song, Zhiyong Wu, Bo Li, Chen Dun, Chong Liu, Fuxing Leng, Hanbin Wang, Hao Yu, Haobin Chen, Hongyi Guo, Jing Su, Jingjia Huang, Kai Shen, Kaiyu Shi, Lin Yan, Peiyao Zhao, Pengfei Liu, Qinghao Ye, Renjie Zheng, Way…

UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have shown promise by unifying perception, reasoning, action, and memory through end-to-end learning, open problems remain in data scalability, multi-turn reinforcement learning (RL), the limitations of GUI-only operation, and environment stability. In this technical report, we present UI-TARS-2, a native GUI-centered agent …

OmniActor: A Generalist GUI and Embodied Agent for 2D&3D Worlds
Longrong Yang, Zhixiong Zeng, Yufeng Zhong, Jing Huang, Liming Zheng, Lei Chen, Haibo Qiu, Zequn Qin, Lin Ma, Xi Li
https://arxiv.org/abs/2509.02322

OmniActor: A Generalist GUI and Embodied Agent for 2D&3D Worlds
Multimodal large language models are evolving toward multimodal agents capable of proactively executing tasks. Most agent research focuses on GUI or embodied scenarios, which correspond to agents interacting with 2D virtual worlds or 3D real worlds, respectively. However, many complex tasks typically require agents to interleavely interact with these two types of environment. We initially mix GUI and embodied data to train, but find the performance degeneration brought by the data conflict. Fur…

Realistic Environmental Injection Attacks on GUI Agents
Yitong Zhang, Ximo Li, Liyi Cai, Jia Li
https://arxiv.org/abs/2509.11250 https://arxiv.org/pdf/2509…

Realistic Environmental Injection Attacks on GUI Agents
GUI agents built on LVLMs are increasingly used to interact with websites. However, their exposure to open-world content makes them vulnerable to Environmental Injection Attacks (EIAs) that hijack agent behavior via webpage elements. Many recent studies assume the attacker to be a regular user who can only upload a single trigger image, which is more realistic than earlier assumptions of website-level administrative control. However, these works still fall short of realism: (1) the trigger's po…

Revisit of the electromagnetic correction to $\tau\to\pi\pi\nu_\tau$ and its implication for muon $g-2$ based on $\tau$ data
Zhi-Xin Li, Ao Li, Jin Hao, Chun-Gui Duan, Zhi-Hui Guo
https://arxiv.org/abs/2510.04172

Revisit of the electromagnetic correction to $τ\toππν_τ$ and its implication for muon $g-2$ based on $τ$ data
In this work we focus on the evaluation of the leading-order hadronic vacuum polarization contribution from the $ππ$ channel to the muon anomalous magnetic moment $a_μ$ by using the experimental $τ\toππν_τ$ data. The isospin breaking corrections play the decisive role in this approach of computing $a_μ$. One of such important isospin breaking sources is the long-distance electromagnetic correction factor $G_{\rm EM}$ of the $τ\toππν_τ$ process from the real photon radiation. The l…

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…

EVDI : Event-based Video Deblurring and Interpolation via Self-Supervised Learning
Chi Zhang, Xiang Zhang, Chenxu Jiang, Gui-Song Xia, Lei Yu
https://arxiv.org/abs/2509.08260 h…

EVDI++: Event-based Video Deblurring and Interpolation via Self-Supervised Learning
Frame-based cameras with extended exposure times often produce perceptible visual blurring and information loss between frames, significantly degrading video quality. To address this challenge, we introduce EVDI++, a unified self-supervised framework for Event-based Video Deblurring and Interpolation that leverages the high temporal resolution of event cameras to mitigate motion blur and enable intermediate frame prediction. Specifically, the Learnable Double Integral (LDI) network is designed …

Search-R3: Unifying Reasoning and Embedding Generation in Large Language Models
Yuntao Gui, James Cheng
https://arxiv.org/abs/2510.07048 https://arxiv.org/…

Search-R3: Unifying Reasoning and Embedding Generation in Large Language Models
Despite their remarkable natural language understanding capabilities, Large Language Models (LLMs) have been underutilized for retrieval tasks. We present Search-R3, a novel framework that addresses this limitation by adapting LLMs to generate search embeddings as a direct output of their reasoning process. Our approach exploits LLMs' chain-of-thought capabilities, allowing them to produce more effective embeddings by reasoning step-by-step through complex semantic analyses. We implement this t…

From KP-I Lump Solution to Travelling wave of 3D Gravity Capillary Water wave problem
Changfeng Gui, Shanfa Lai, Yong Liu, Juncheng Wei, Wen Yang
https://arxiv.org/abs/2509.06084

From KP-I Lump Solution to Travelling wave of 3D Gravity Capillary Water wave problem
In this paper, we study the three-dimensional gravity-capillary water wave problem involving an irrotational, perfect fluid with gravity and surface tension. We focus on steady waves propagating uniformly in one direction. Assuming constant wave speed and water depth, we analyze the fluid's velocity potential and boundary conditions. Using the Kadomtsev-Petviashvili (KP)-I equation as a simplified model, we show that, within a specific parameter range, the problem admits a fully localized solit…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/5]:
- \emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition
Yao Lu, Chunfeng Sun, Dongwei Xu, Yun Lin, Qi Xuan, Guan Gui

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…

LaTCoder: Converting Webpage Design to Code with Layout-as-Thought
Yi Gui, Zhen Li, Zhongyi Zhang, Guohao Wang, Tianpeng Lv, Gaoyang Jiang, Yi Liu, Dongping Chen, Yao Wan, Hongyu Zhang, Wenbin Jiang, Xuanhua Shi, Hai Jin
https://arxiv.org/abs/2508.03560

LaTCoder: Converting Webpage Design to Code with Layout-as-Thought
Converting webpage designs into code (design-to-code) plays a vital role in User Interface (UI) development for front-end developers, bridging the gap between visual design and functional implementation. While recent Multimodal Large Language Models (MLLMs) have shown significant potential in design-to-code tasks, they often fail to accurately preserve the layout during code generation. To this end, we draw inspiration from the Chain-of-Thought (CoT) reasoning in human cognition and propose LaT…

Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding
Wanfu Wang, Qipeng Huang, Guangquan Xue, Xiaobo Liang, Juntao Li
https://arxiv.org/abs/2509.04243

Learning Active Perception via Self-Evolving Preference Optimization for GUI Grounding
Vision Language Models (VLMs) have recently achieved significant progress in bridging visual perception and linguistic reasoning. Recently, OpenAI o3 model introduced a zoom-in search strategy that effectively elicits active perception capabilities in VLMs, improving downstream task performance. However, enabling VLMs to reason effectively over appropriate image regions remains a core challenge in GUI grounding, particularly under high-resolution inputs and complex multi-element visual interact…

Real-Time Power electronics Control and Monitoring with TI F28379D DSC and GUI Composer
Ilyas Bennia, Lotfi Baghli, Ehsan Jamshidpour, Abdelkader Mechernene, Jean-Philippe Martin, Driss Yousfi
https://arxiv.org/abs/2509.25008

Real-Time Power electronics Control and Monitoring with TI F28379D DSC and GUI Composer
This paper details the implementation and experimental validation of a real-time control system for a three-phase induction motor using the Texas Instruments TMS320F28379D microcontroller. The system integrates pulse-width modulation (PWM) generation, analog-to-digital conversion (ADC), digital-to-analog conversion (DAC), and quadrature encoder feedback to facilitate precise control under various strategies. A current sensing solution based on the AMC1301 isolation amplifier and shunt resistor …

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…

Ferret-UI Lite: Lessons from Building Small On-Device GUI Agents
Zhen Yang, Zi-Yi Dou, Di Feng, Forrest Huang, Anh Nguyen, Keen You, Omar Attia, Yuhao Yang, Michael Feng, Haotian Zhang, Ram Ramrakhya, Chao Jia, Jeffrey Nichols, Alexander Toshev, Yinfei Yang, Zhe Gan
https://arxiv.org/abs/2509.26539…

Ferret-UI Lite: Lessons from Building Small On-Device GUI Agents
Developing autonomous agents that effectively interact with Graphic User Interfaces (GUIs) remains a challenging open problem, especially for small on-device models. In this paper, we present Ferret-UI Lite, a compact, end-to-end GUI agent that operates across diverse platforms, including mobile, web, and desktop. Utilizing techniques optimized for developing small models, we build our 3B Ferret-UI Lite agent through curating a diverse GUI data mixture from real and synthetic sources, strengthe…

Log2Plan: An Adaptive GUI Automation Framework Integrated with Task Mining Approach
Seoyoung Lee, Seonbin Yoon, Seongbeen Lee, Hyesoo Kim, Joo Yong Sim
https://arxiv.org/abs/2509.22137

Log2Plan: An Adaptive GUI Automation Framework Integrated with Task Mining Approach
GUI task automation streamlines repetitive tasks, but existing LLM or VLM-based planner-executor agents suffer from brittle generalization, high latency, and limited long-horizon coherence. Their reliance on single-shot reasoning or static plans makes them fragile under UI changes or complex tasks. Log2Plan addresses these limitations by combining a structured two-level planning framework with a task mining approach over user behavior logs, enabling robust and adaptable GUI automation. Log2Plan…

Well-Posedness of the Cauchy Problem for First-order Quasilinear Equations with Non-Lipschitz Source Terms and Its Applications
Gaowei Cao, Gui-Qiang G. Chen, Wei Xiang, Xiaozhou Yang
https://arxiv.org/abs/2509.06020

Well-Posedness of the Cauchy Problem for First-order Quasilinear Equations with Non-Lipschitz Source Terms and Its Applications
We are concerned with the well-posedness of the Cauchy problem for the first-order quasilinear equations with non-Lipschitz source terms and the global structures of the multi-dimensional Riemann solutions. For such quasilinear equations with initial data in $L^\infty$, when the source term $g(t, x, u)$ is only right-Lipschitz (not necessarily left-Lipschitz) in $u$, we first prove that the Kruzkov entropy condition is sufficient to guarantee the well-posdeness of entropy solutions. Next, we an…

RISK: A Framework for GUI Agents in E-commerce Risk Management
Renqi Chen, Zeyin Tao, Jianming Guo, Jingzhe Zhu, Yiheng Peng, Qingqing Sun, Tianyi Zhang, Shuai Chen
https://arxiv.org/abs/2509.21982

RISK: A Framework for GUI Agents in E-commerce Risk Management
E-commerce risk management requires aggregating diverse, deeply embedded web data through multi-step, stateful interactions, which traditional scraping methods and most existing Graphical User Interface (GUI) agents cannot handle. These agents are typically limited to single-step tasks and lack the ability to manage dynamic, interactive content critical for effective risk assessment. To address this challenge, we introduce RISK, a novel framework designed to build and deploy GUI agents for this…

Blueprint First, Model Second: A Framework for Deterministic LLM Workflow
Libin Qiu, Yuhang Ye, Zhirong Gao, Xide Zou, Junfu Chen, Ziming Gui, Weizhi Huang, Xiaobo Xue, Wenkai Qiu, Kun Zhao
https://arxiv.org/abs/2508.02721

Blueprint First, Model Second: A Framework for Deterministic LLM Workflow
While powerful, the inherent non-determinism of large language model (LLM) agents limits their application in structured operational environments where procedural fidelity and predictable execution are strict requirements. This limitation stems from current architectures that conflate probabilistic, high-level planning with low-level action execution within a single generative process. To address this, we introduce the Source Code Agent framework, a new paradigm built on the "Blueprint First, M…

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…

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\…

R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?
Yi Lu, Jianing Wang, Linsen Guo, Wei He, Hongyin Tang, Tao Gui, Xuanjing Huang, Xuezhi Cao, Wei Wang, Xunliang Cai
https://arxiv.org/abs/2510.08189

R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?
Recent trends in test-time scaling for reasoning models (e.g., OpenAI o1, DeepSeek-R1) have led to remarkable improvements through long Chain-of-Thought (CoT). However, existing benchmarks mainly focus on immediate, single-horizon tasks, failing to adequately evaluate models' ability to understand and respond to complex, long-horizon scenarios. To address this incomplete evaluation of Large Reasoning Models (LRMs), we propose R-HORIZON, a method designed to stimulate long-horizon reasoning beha…

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…

An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models
Rujie Dai, Peizhuo Lv, Yujiang Gui, Qiujian Lv, Yuanyuan Qiao, Yan Wang, Degang Sun, Weiqing Huang, Yingjiu Li, XiaoFeng Wang
https://arxiv.org/abs/2509.01271

An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models
Advanced Persistent Threats (APTs) are prolonged, stealthy intrusions by skilled adversaries that compromise high-value systems to steal data or disrupt operations. Reconstructing complete attack chains from massive, heterogeneous logs is essential for effective attack investigation, yet existing methods suffer from poor platform generality, limited generalization to evolving tactics, and an inability to produce analyst-ready reports. Large Language Models (LLMs) offer strong semantic understan…

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

GenPilot: A Multi-Agent System for Test-Time Prompt Optimization in Image Generation
Wen Ye, Zhaocheng Liu, Yuwei Gui, Tingyu Yuan, Yunyue Su, Bowen Fang, Chaoyang Zhao, Qiang Liu, Liang Wang
https://arxiv.org/abs/2510.07217

GenPilot: A Multi-Agent System for Test-Time Prompt Optimization in Image Generation
Text-to-image synthesis has made remarkable progress, yet accurately interpreting complex and lengthy prompts remains challenging, often resulting in semantic inconsistencies and missing details. Existing solutions, such as fine-tuning, are model-specific and require training, while prior automatic prompt optimization (APO) approaches typically lack systematic error analysis and refinement strategies, resulting in limited reliability and effectiveness. Meanwhile, test-time scaling methods opera…

D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents
Hongze Mi, Yibo Feng, Wenjie Lu, Yuqi Wang, Jinyuan Li, Song Cao, He Cui, Tengfei Tian, Xuelin Zhang, Haotian Luo, Di Sun, Naiqiang Tan, Gang Pan
https://arxiv.org/abs/2509.21799

D-Artemis: A Deliberative Cognitive Framework for Mobile GUI Multi-Agents
Graphical User Interface (GUI) agents aim to automate a wide spectrum of human tasks by emulating user interaction. Despite rapid advancements, current approaches are hindered by several critical challenges: data bottleneck in end-to-end training, high cost of delayed error detection, and risk of contradictory guidance. Inspired by the human cognitive loop of Thinking, Alignment, and Reflection, we present D-Artemis -- a novel deliberative framework in this paper. D-Artemis leverages a fine-gra…

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…

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
Jingyu Tang, Chaoran Chen, Jiawen Li, Zhiping Zhang, Bingcan Guo, Ibrahim Khalilov, Simret Araya Gebreegziabher, Bingsheng Yao, Dakuo Wang, Yanfang Ye, Tianshi Li, Ziang Xiao, Yaxing Yao, Toby Jia-Jun Li
https://arxiv.org/abs/…

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks from high-level intents, understanding how dark patterns affect agents is increasingly important. We present a two-phase empirical study examining how agents, human participants, and human-AI teams respond to 16 types of dark patterns across diverse scenario…

ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Gaole Dai, Shiqi Jiang, Ting Cao, Yuqing Yang, Yuanchun Li, Rui Tan, Mo Li, Lili Qiu
https://arxiv.org/abs/2509.21823

ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents, where access to ground-truth trajectories or application databases is often unavailable, and static trajectory-based LLM-as-a-Judge approaches suffer from limited accuracy. To address these challenges, we propose ProRe, a proactive reward system that leverages a general-purpose reasoner and domain-specific evaluator a…

Orcust: Stepwise-Feedback Reinforcement Learning for GUI Agent
Junyu Lu, Songxin Zhang, Zejian Xie, Zhuoyang Song, Jiaxing Zhang
https://arxiv.org/abs/2509.17917 https://…

Orcust: Stepwise-Feedback Reinforcement Learning for GUI Agent
Recent advances in GUI agents have achieved remarkable grounding and action-prediction performance, yet existing models struggle with unreliable reward signals and limited online trajectory generation. In this paper, we introduce Orcust, a framework that integrates Principle-Constrained Reward Modeling (PCRM) and Online VM-Grounded Trajectory Construction (OVTC) to enhance reasoning reliability and data efficiency in interactive GUI tasks. We leverages environment-verifiable and LLM-derived pri…

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…

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…

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
[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

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
Zongru Wu, Rui Mao, Zhiyuan Tian, Pengzhou Cheng, Tianjie Ju, Zheng Wu, Lingzhong Dong, Haiyue Sheng, Zhuosheng Zhang, Gongshen Liu
https://arxiv.org/abs/2509.13615

See, Think, Act: Teaching Multimodal Agents to Effectively Interact with GUI by Identifying Toggles
The advent of multimodal agents facilitates effective interaction within graphical user interface (GUI), especially in ubiquitous GUI control. However, their inability to reliably execute toggle control instructions remains a key bottleneck. To investigate this, we construct a state control benchmark with binary toggle instructions from public datasets. Evaluations of existing agents demonstrate their unreliability, particularly when the current toggle state already matches the desired state. T…

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

AutoMaAS: Self-Evolving Multi-Agent Architecture Search for Large Language Models
Bo Ma, Hang Li, ZeHua Hu, XiaoFan Gui, LuYao Liu, Simon Liu
https://arxiv.org/abs/2510.02669 ht…

AutoMaAS: Self-Evolving Multi-Agent Architecture Search for Large Language Models
Multi-agent systems powered by large language models have demonstrated remarkable capabilities across diverse domains, yet existing automated design approaches seek monolithic solutions that fail to adapt resource allocation based on query complexity and domain requirements. This paper introduces AutoMaAS, a self-evolving multi-agent architecture search framework that leverages neural architecture search principles to automatically discover optimal agent configurations through dynamic operator …

Towards Adversarial Training under Hyperspectral Images
Weihua Zhang, Chengze Jiang, Jie Gui, Lu Dong
https://arxiv.org/abs/2510.01014 https://arxiv.org/pd…

Towards Adversarial Training under Hyperspectral Images
Recent studies have revealed that hyperspectral classification models based on deep learning are highly vulnerable to adversarial attacks, which pose significant security risks. Although several approaches have attempted to enhance adversarial robustness by modifying network architectures, these methods often rely on customized designs that limit scalability and fail to defend effectively against strong attacks. To address these challenges, we introduce adversarial training to the hyperspectral…

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

InfraMind: A Novel Exploration-based GUI Agentic Framework for Mission-critical Industrial Management
Liangtao Lin, Zhaomeng Zhu, Tianwei Zhang, Yonggang Wen
https://arxiv.org/abs/2509.13704

InfraMind: A Novel Exploration-based GUI Agentic Framework for Mission-critical Industrial Management
Mission-critical industrial infrastructure, such as data centers, increasingly depends on complex management software. Its operations, however, pose significant challenges due to the escalating system complexity, multi-vendor integration, and a shortage of expert operators. While Robotic Process Automation (RPA) offers partial automation through handcrafted scripts, it suffers from limited flexibility and high maintenance costs. Recent advances in Large Language Model (LLM)-based graphical user…