Tootfinder

Empowering IoT Firmware Secure Update with Customization Rights
Weihao Chen, Yansong Gao, Boyu Kuang, Jin B. Hong, Yuqing Zhang, Anmin Fu
https://arxiv.org/abs/2507.19367 https:…

Empowering IoT Firmware Secure Update with Customization Rights
Firmware updates remain the primary line of defense for IoT devices; however, the update channel itself has become a well-established attack vector. Existing defenses mainly focus on securing monolithic firmware images, leaving module-level customization -a growing user demand-largely unprotected and insufficiently explored. To address this gap, we conduct a pilot study on the update workflows of 200 Linux-based IoT devices across 23 vendors, uncovering five previously undocumented vulnerabilit…

KinemaFX: A Kinematic-Driven Interactive System for Particle Effect Exploration and Customization
Yifei Zhang, Lin-Ping Yuan, Yuheng Zhao, Jielin Feng, Siming Chen
https://arxiv.org/abs/2507.19782

KinemaFX: A Kinematic-Driven Interactive System for Particle Effect Exploration and Customization
Particle effects are widely used in games and animation to simulate natural phenomena or stylized visual effects. However, creating effect artworks is challenging for non-expert users due to their lack of specialized skills, particularly in finding particle effects with kinematic behaviors that match their intent. To address these issues, we present KinemaFX, a kinematic-driven interactive system, to assist non-expert users in constructing customized particle effect artworks. We propose a conce…

Has anyone used Windhawk?
https://windhawk.net/
It's a tweak/mod installer for Windows. Like Cydia or SIMBL or Application Enhancer. Released in 2022.
I'm impressed by the number of mods they have listed. Each mod has visible source code, a single file with metadata in comments, l…

H-PRM: A Pluggable Hotword Pre-Retrieval Module for Various Speech Recognition Systems
Huangyu Dai, Lingtao Mao, Ben Chen, Zihan Wang, Zihan Liang, Ying Han, Chenyi Lei, Han Li
https://arxiv.org/abs/2508.18295

H-PRM: A Pluggable Hotword Pre-Retrieval Module for Various Speech Recognition Systems
Hotword customization is crucial in ASR to enhance the accuracy of domain-specific terms. It has been primarily driven by the advancements in traditional models and Audio large language models (LLMs). However, existing models often struggle with large-scale hotwords, as the recognition rate drops dramatically with the number of hotwords increasing. In this paper, we introduce a novel hotword customization system that utilizes a hotword pre-retrieval module (H-PRM) to identify the most relevant …

🔧 Fine-grained control
over app logic through visual interface or description-based modifications
📱 Instant sharing capabilities
allowing others to use your apps with their #Google account
📚 Demo gallery
with starter templates for immediate use or customization
🚀 Currently available in US-only public beta
for rapid

CapTune: Adapting Non-Speech Captions With Anchored Generative Models
Jeremy Zhengqi Huang, Calu\~a de Lacerda Pataca, Liang-Yuan Wu, Dhruv Jain
https://arxiv.org/abs/2508.19971

CapTune: Adapting Non-Speech Captions With Anchored Generative Models
Non-speech captions are essential to the video experience of deaf and hard of hearing (DHH) viewers, yet conventional approaches often overlook the diversity of their preferences. We present CapTune, a system that enables customization of non-speech captions based on DHH viewers' needs while preserving creator intent. CapTune allows caption authors to define safe transformation spaces using concrete examples and empowers viewers to personalize captions across four dimensions: level of detail, e…

Personalized Mental State Evaluation in Human-Robot Interaction using Federated Learning
Andrea Bussolan, Oliver Avram, Andrea Pignata, Gianvito Urgese, Stefano Baraldo, Anna Valente
https://arxiv.org/abs/2506.20212

Personalized Mental State Evaluation in Human-Robot Interaction using Federated Learning
With the advent of Industry 5.0, manufacturers are increasingly prioritizing worker well-being alongside mass customization. Stress-aware Human-Robot Collaboration (HRC) plays a crucial role in this paradigm, where robots must adapt their behavior to human mental states to improve collaboration fluency and safety. This paper presents a novel framework that integrates Federated Learning (FL) to enable personalized mental state evaluation while preserving user privacy. By leveraging physiological…

ACME: Adaptive Customization of Large Models via Distributed Systems
Ziming Dai, Chao Qiu, Fei Gao, Yunfeng Zhao, Xiaofei Wang
https://arxiv.org/abs/2507.14802

ACME: Adaptive Customization of Large Models via Distributed Systems
Pre-trained Transformer-based large models have revolutionized personal virtual assistants, but their deployment in cloud environments faces challenges related to data privacy and response latency. Deploying large models closer to the data and users has become a key research area to address these issues. However, applying these models directly often entails significant difficulties, such as model mismatching, resource constraints, and energy inefficiency. Automated design of customized models i…

Pre-training Time Series Models with Stock Data Customization
Mengyu Wang, Tiejun Ma, Shay B. Cohen
https://arxiv.org/abs/2506.16746 https://

Pre-training Time Series Models with Stock Data Customization
Stock selection, which aims to predict stock prices and identify the most profitable ones, is a crucial task in finance. While existing methods primarily focus on developing model structures and building graphs for improved selection, pre-training strategies remain underexplored in this domain. Current stock series pre-training follows methods from other areas without adapting to the unique characteristics of financial data, particularly overlooking stock-specific contextual information and the…

IC-Custom: Diverse Image Customization via In-Context Learning
Yaowei Li, Xiaoyu Li, Zhaoyang Zhang, Yuxuan Bian, Gan Liu, Xinyuan Li, Jiale Xu, Wenbo Hu, Yating Liu, Lingen Li, Jing Cai, Yuexian Zou, Yancheng He, Ying Shan
https://arxiv.org/abs/2507.01926

IC-Custom: Diverse Image Customization via In-Context Learning
Image customization, a crucial technique for industrial media production, aims to generate content that is consistent with reference images. However, current approaches conventionally separate image customization into position-aware and position-free customization paradigms and lack a universal framework for diverse customization, limiting their applications across various scenarios. To overcome these limitations, we propose IC-Custom, a unified framework that seamlessly integrates position-awa…