Tootfinder

I'm just reviewing some old(er) video I recorded quite a while ago ... and I admit that I'm eager to record in higher quality!
But hey, it's all a learning curve. I'm not feeling bad about the bad quality. I regard it pretty nice to see the advancement over time!
https://video.franzgraf.de/w/r3XH…

The journey of learning is transformative, fueling curiosity and sparking growth. Knowledge lets us transcend limits and transform challenges into thrilling adventures. 🚀
Where has your curiosity led you lately? Share your stories!
#LifelongLearning #CuriosityJourney

South Korea's AI textbook program, meant to personalize learning, was rolled back after just four months after complaints about inaccuracies and extra workload (Junhyup Kwon/Rest of World)
https://restofworld.org/2025/south-korea-ai-textbook/

AI-powered textbooks fail to make the grade in South Korea
South Korea’s AI learning program was rolled back after just four months following a backlash from teachers, students, and parents, underlining the challenges in embedding the technology in education.

Trying very hard to maintain my calm.
☑️ Hollywood stars, politicians pay tribute to Rob Reiner and his wife following their shocking deaths
Reiner, 78, was found dead alongside wife, Michele Singer Reiner, 68, at their home in Los Angeles on Sunday.
https://www.<…

Rob Reiner death: Tributes pour in for filmmaker and his wife, Michele
Hollywood luminaries and political heavyweights expressed their shock and sadness Sunday night upon learning that prolific director Rob Reiner and his wife, Michele Singer Reiner, were found dead in their Los Angeles home.

Refereed Learning
Ran Canetti, Ephraim Linder, Connor Wagaman
https://arxiv.org/abs/2510.05440 https://arxiv.org/pdf/2510.05440

Refereed Learning
We initiate an investigation of learning tasks in a setting where the learner is given access to two competing provers, only one of which is honest. Specifically, we consider the power of such learners in assessing purported properties of opaque models. Following prior work that considers the power of competing provers in different settings, we call this setting refereed learning. After formulating a general definition of refereed learning tasks, we show refereed learning protocols that obtai…

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
Shoeb Joarder, Mohamed Amine Chatti
https://arxiv.org/abs/2510.08395

Human-Centered Development of Indicators for Self-Service Learning Analytics: A Transparency through Exploration Approach
The aim of learning analytics is to turn educational data into insights, decisions, and actions to improve learning and teaching. The reasoning of the provided insights, decisions, and actions is often not transparent to the end-user, and this can lead to trust and acceptance issues when interventions, feedback, and recommendations fail. In this paper, we shed light on achieving transparent learning analytics by following a transparency through exploration approach. To this end, we present the …

UniAPL: A Unified Adversarial Preference Learning Framework for Instruct-Following
FaQiang Qian, WeiKun Zhang, Ziliang Wang, Kang An, Xuhui Zheng, Liangjian Wen, Mengya Gao, Yong Dai, Yichao Wu
https://arxiv.org/abs/2509.25148

UniAPL: A Unified Adversarial Preference Learning Framework for Instruct-Following
Shaping powerful LLMs to be beneficial and safe is central to AI alignment. We argue that post-training alignment is fundamentally a unified Preference Learning problem, involving two modalities: demonstrated preferences (e.g., Supervised Fine-Tuning, SFT) and comparative preferences (e.g., Reinforcement Learning, RL).The standard sequential pipeline-SFT followed by RL-is flawed due to a critical distributional mismatch: SFT uses static expert data, but as the policy evolves, its generation dis…

Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans following Omega-3 Fatty Acid Supplementation
Shudong Sun, Aki Hara, Laurel Johnstone, Brian Hallmark, Joseph C. Watkins, Cynthia A. Thomson, Susan M. Schembre, Susan Sergeant, Jason Umans, Guang Yao, Hao Helen Zhang, Floyd H. Chilton

Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans following Omega-3 Fatty Acid Supplementation
Conflicting clinical trial results on omega-3 highly unsaturated fatty acids (n-3 HUFA) have prompted uncertainty about their cardioprotective effects. While the VITAL trial found no overall cardiovascular benefit from n-3 HUFA supplementation, its substantial African American (AfAm) enrollment provided a unique opportunity to explore racial differences in response to n-3 HUFA supplementation. The current observational study aimed to simulate randomized clinical trial (RCT) conditions by matchi…

BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
Rui-Yang Zhang, Henry B. Moss, Lachlan Astfalck, Edward Cripps, David S. Leslie
https://arxiv.org/abs/2509.26005

BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
We introduce a formal active learning methodology for guiding the placement of Lagrangian observers to infer time-dependent vector fields -- a key task in oceanography, marine science, and ocean engineering -- using a physics-informed spatio-temporal Gaussian process surrogate model. The majority of existing placement campaigns either follow standard `space-filling' designs or relatively ad-hoc expert opinions. A key challenge to applying principled active learning in this setting is that Lagra…