Tootfinder

CFP reminder: Humanities Bulletin 8.2, November 2025 Special Issue: Reading to Know, Learning to Hear, Engaging in Respect and Love within an Intercultural Frame https://call-for-papers.sas.upenn.edu/cfp/2025/09/1…

Reading a Ruler in the Wild
Yimu Pan, Manas Mehta, Gwen Sincerbeaux, Jeffery A. Goldstein, Alison D. Gernand, James Z. Wang
https://arxiv.org/abs/2507.07077

Reading a Ruler in the Wild
Accurately converting pixel measurements into absolute real-world dimensions remains a fundamental challenge in computer vision and limits progress in key applications such as biomedicine, forensics, nutritional analysis, and e-commerce. We introduce RulerNet, a deep learning framework that robustly infers scale "in the wild" by reformulating ruler reading as a unified keypoint-detection problem and by representing the ruler with geometric-progression parameters that are invariant to perspectiv…

HEMA: A Hands-on Exploration Platform for MEMS Sensor Attacks
Bhagawat Baanav Yedla Ravi, Md Rafiul Kabir, Sandip Ray
https://arxiv.org/abs/2507.06439 http…

HEMA: A Hands-on Exploration Platform for MEMS Sensor Attacks
Automotive safety and security are paramount in the rapidly advancing landscape of vehicular technology. Building safe and secure vehicles demands a profound understanding of automotive systems, particularly in safety and security. Traditional learning approaches, such as reading materials or observing demonstrations, often fail to provide the practical, hands-on experience essential for developing this expertise. For novice users, gaining access to automotive-grade systems and mastering their …

Was anyone else taught this? I learnt ITA in my earliest education. Unlike the people profiled in the article I've never had any trouble with spelling or any aspect of learning or using English and I'd wondered if that was *because* I'd been taught ITA but judging by this article I was just lucky!

Opportunities and Challenges of LLMs in Education: An NLP Perspective
Sowmya Vajjala, Bashar Alhafni, Stefano Bann\`o, Kaushal Kumar Maurya, Ekaterina Kochmar
https://arxiv.org/abs/2507.22753

Opportunities and Challenges of LLMs in Education: An NLP Perspective
Interest in the role of large language models (LLMs) in education is increasing, considering the new opportunities they offer for teaching, learning, and assessment. In this paper, we examine the impact of LLMs on educational NLP in the context of two main application scenarios: {\em assistance} and {\em assessment}, grounding them along the four dimensions -- reading, writing, speaking, and tutoring. We then present the new directions enabled by LLMs, and the key challenges to address. We envi…

Detecting COPD Through Speech Analysis: A Dataset of Danish Speech and Machine Learning Approach
Cuno Sankey-Olsen, Rasmus Hvass Olesen, Tobias Oliver Eberhard, Andreas Triantafyllopoulos, Bj\"orn Schuller, Ilhan Aslan
https://arxiv.org/abs/2508.02354

Detecting COPD Through Speech Analysis: A Dataset of Danish Speech and Machine Learning Approach
Chronic Obstructive Pulmonary Disease (COPD) is a serious and debilitating disease affecting millions around the world. Its early detection using non-invasive means could enable preventive interventions that improve quality of life and patient outcomes, with speech recently shown to be a valuable biomarker. Yet, its validity across different linguistic groups remains to be seen. To that end, audio data were collected from 96 Danish participants conducting three speech tasks (reading, coughing, …

CFP reminder: Humanities Bulletin 8.2, November 2025 Special Issue: Reading to Know, Learning to Hear, Engaging in Respect and Love within an Intercultural Frame
https://ift.tt/7DIRZst
updated: Thursday, September 11, 2025 - 3:35pmfull name / name of organization: London Academic…
via Input 4 RELCFP

Ark: An Open-source Python-based Framework for Robot Learning
Magnus Dierking, Christopher E. Mower, Sarthak Das, Huang Helong, Jiacheng Qiu, Cody Reading, Wei Chen, Huidong Liang, Huang Guowei, Jan Peters, Quan Xingyue, Jun Wang, Haitham Bou-Ammar
https://arxiv.org/abs/2506.21628

Ark: An Open-source Python-based Framework for Robot Learning
Robotics has made remarkable hardware strides-from DARPA's Urban and Robotics Challenges to the first humanoid-robot kickboxing tournament-yet commercial autonomy still lags behind progress in machine learning. A major bottleneck is software: current robot stacks demand steep learning curves, low-level C/C++ expertise, fragmented tooling, and intricate hardware integration, in stark contrast to the Python-centric, well-documented ecosystems that propelled modern AI. We introduce ARK, an open-so…

Detecting Reading-Induced Confusion Using EEG and Eye Tracking
Haojun Zhuang, D\"unya Baradari, Nataliya Kosmyna, Arnav Balyan, Constanze Albrecht, Stephanie Chen, Pattie Maes
https://arxiv.org/abs/2508.14442

Detecting Reading-Induced Confusion Using EEG and Eye Tracking
Humans regularly navigate an overwhelming amount of information via text media, whether reading articles, browsing social media, or interacting with chatbots. Confusion naturally arises when new information conflicts with or exceeds a reader's comprehension or prior knowledge, posing a challenge for learning. In this study, we present a multimodal investigation of reading-induced confusion using EEG and eye tracking. We collected neural and gaze data from 11 adult participants as they read shor…

CFP reminder: Humanities Bulletin 8.2, November 2025 Special Issue: Reading to Know, Learning to Hear, Engaging in Respect and Love within an Intercultural Frame
https://ift.tt/7DIRZst
updated: Thursday, September 11, 2025 - 3:35pmfull name / name of organization: London Academic…
via Input 4 RELCFP

From Model to Classroom: Evaluating Generated MCQs for Portuguese with Narrative and Difficulty Concerns
Bernardo Leite, Henrique Lopes Cardoso, Pedro Pinto, Abel Ferreira, Lu\'is Abreu, Isabel Rangel, Sandra Monteiro
https://arxiv.org/abs/2506.15598

From Model to Classroom: Evaluating Generated MCQs for Portuguese with Narrative and Difficulty Concerns
While MCQs are valuable for learning and evaluation, manually creating them with varying difficulty levels and targeted reading skills remains a time-consuming and costly task. Recent advances in generative AI provide an opportunity to automate MCQ generation efficiently. However, assessing the actual quality and reliability of generated MCQs has received limited attention -- particularly regarding cases where generation fails. This aspect becomes particularly important when the generated MCQs …

More Expert-like Eye Gaze Movement Patterns are Related to Better X-ray Reading
Pingjing Yang, Jennifer Cromley, Jana Diesner
https://arxiv.org/abs/2507.18637 https://

More Expert-like Eye Gaze Movement Patterns are Related to Better X-ray Reading
Understanding how novices acquire and hone visual search skills is crucial for developing and optimizing training methods across domains. Network analysis methods can be used to analyze graph representations of visual expertise. This study investigates the relationship between eye-gaze movements and learning outcomes among undergraduate dentistry students who were diagnosing dental radiographs over multiple semesters. We use network analysis techniques to model eye-gaze scanpaths as directed gr…

Futurity as Infrastructure: A Techno-Philosophical Interpretation of the AI Lifecycle
Mark Cote, Susana Aires
https://arxiv.org/abs/2508.15680 https://arxi…

Futurity as Infrastructure: A Techno-Philosophical Interpretation of the AI Lifecycle
This paper argues that a techno-philosophical reading of the EU AI Act provides insight into the long-term dynamics of data in AI systems, specifically, how the lifecycle from ingestion to deployment generates recursive value chains that challenge existing frameworks for Responsible AI. We introduce a conceptual tool to frame the AI pipeline, spanning data, training regimes, architectures, feature stores, and transfer learning. Using cross-disciplinary methods, we develop a technically grounded…

A statistical framework for dynamic cognitive diagnosis in digital learning environments
Yawen Ma, Anastasia Ushakova, Kate Cain, Gabriel Wallin
https://arxiv.org/abs/2506.14531

A statistical framework for dynamic cognitive diagnosis in digital learning environments
Reading is foundational for educational, employment, and economic outcomes, but a persistent proportion of students globally struggle to develop adequate reading skills. Some countries promote digital tools to support reading development, alongside regular classroom instruction. Such tools generate rich log data capturing students' behaviour and performance. This study proposes a dynamic cognitive diagnostic modeling (CDM) framework based on restricted latent class models to trace students' tim…