Tootfinder

Training camp overreactions heading into Week 1 of preseason: Shedeur Sanders playing for roster spot?

https://www.cbssports.com/nfl/news/trainin

Estimation of Resistance Training RPE using Inertial Sensors and Electromyography
James Thomas, Johan Walhstr\"om
https://arxiv.org/abs/2510.03197 https://

Estimation of Resistance Training RPE using Inertial Sensors and Electromyography
Accurate estimation of rating of perceived exertion (RPE) can enhance resistance training through personalized feedback and injury prevention. This study investigates the application of machine learning models to estimate RPE during single-arm dumbbell bicep curls, using data from wearable inertial and electromyography (EMG) sensors. A custom dataset of 69 sets and over 1000 repetitions was collected, with statistical features extracted for model training. Among the models evaluated, a random f…

Dynamic Prompt Generation for Interactive 3D Medical Image Segmentation Training
Tidiane Camaret Ndir, Alexander Pfefferle, Robin Tibor Schirrmeister
https://arxiv.org/abs/2510.03189

Dynamic Prompt Generation for Interactive 3D Medical Image Segmentation Training
Interactive 3D biomedical image segmentation requires efficient models that can iteratively refine predictions based on user prompts. Current foundation models either lack volumetric awareness or suffer from limited interactive capabilities. We propose a training strategy that combines dynamic volumetric prompt generation with content-aware adaptive cropping to optimize the use of the image encoder. Our method simulates realistic user interaction patterns during training while addressing the co…

GPT-5 will use "safe completions", a training approach to maximize model helpfulness within safety constraints and an improvement over refusal-based training (OpenAI)
https://openai.com/index/gpt-5-safe-completions

A Pleasant Training Camp Surprise for Carroll, Raiders https://www.si.com/nfl/raiders/las-vegas-training-camp-pete-carroll-chip-kelly-patrick-graham

EntropyLong: Effective Long-Context Training via Predictive Uncertainty
Junlong Jia, Ziyang Chen, Xing Wu, Chaochen Gao, Zijia Lin, Debing Zhang, Songlin Hu, Binghui Guo
https://arxiv.org/abs/2510.02330

EntropyLong: Effective Long-Context Training via Predictive Uncertainty
Training long-context language models to capture long-range dependencies requires specialized data construction. Current approaches, such as generic text concatenation or heuristic-based variants, frequently fail to guarantee genuine long-range dependencies. We propose EntropyLong, a novel data construction method that leverages predictive uncertainty to verify dependency quality. Our approach identifies high-entropy positions in documents, retrieves semantically relevant contexts from large co…

Aidan Hutchinson's dominance at Lions training camp forces Detroit to implement 'Hutch Rule' in practice

https://www.cbssports.com/nfl/news/aidan-h…

TeachLM: Post-Training LLMs for Education Using Authentic Learning Data
Janos Perczel, Jin Chow, Dorottya Demszky
https://arxiv.org/abs/2510.05087 https://…

TeachLM: Post-Training LLMs for Education Using Authentic Learning Data
The promise of generative AI to revolutionize education is constrained by the pedagogical limits of large language models (LLMs). A major issue is the lack of access to high-quality training data that reflect the learning of actual students. Prompt engineering has emerged as a stopgap, but the ability of prompts to encode complex pedagogical strategies in rule-based natural language is inherently limited. To address this gap we introduce TeachLM - an LLM optimized for teaching through parameter…

Why Drake Maye's best day of training camp could foreshadow second-year fireworks for Patriots quarterback

https://www.cbssports.com/nfl/news/drake-m

'He's in the best shape of his life': Ranking the most popular NFL training camp and preseason clichés

https://www.cbssports.com/nfl/news/hes-in-