Tootfinder

Pref-GUIDE: Continual Policy Learning from Real-Time Human Feedback via Preference-Based Learning
Zhengran Ji, Boyuan Chen
https://arxiv.org/abs/2508.07126 https://

Pref-GUIDE: Continual Policy Learning from Real-Time Human Feedback via Preference-Based Learning
Training reinforcement learning agents with human feedback is crucial when task objectives are difficult to specify through dense reward functions. While prior methods rely on offline trajectory comparisons to elicit human preferences, such data is unavailable in online learning scenarios where agents must adapt on the fly. Recent approaches address this by collecting real-time scalar feedback to guide agent behavior and train reward models for continued learning after human feedback becomes un…

Major wine regions could disappear from global warming, Europe to be hit especially hard - Science Feedback
https://science.feedback.org/major-wine-regions-could-disappear-from-global-warming-europe-to-be-hit-especially-hard/

We're going to need so much community and mutual aid to deal with the coming climate change reckoning combined with the complete abandonment by the US government. https://fed.brid.gy/r/https://bsky.app/profile/did:plc:f7utvjkqbgwfj…

Smart Device Development for Gait Monitoring: Multimodal Feedback in an Interactive Foot Orthosis, Walking Aid, and Mobile Application
Stefan Resch, Andr\'e Kousha, Anna Carroll, Noah Severinghaus, Felix Rehberg, Marco Zatschker, Yunus S\"oyleyici, Daniel Sanchez-Morillo
https://arxiv.org/abs/2509.09359

Smart Device Development for Gait Monitoring: Multimodal Feedback in an Interactive Foot Orthosis, Walking Aid, and Mobile Application
Smart assistive technologies such as sensor-based footwear and walking aids offer promising opportunities to support rehabilitation through real-time feedback and patient-centered monitoring. However, most orthotic devices remain passive and lack integrated sensing or feedback functionalities, while existing research often focuses on isolated prototypes rather than cohesive, interactive systems. In this work, we present the design and implementation of a novel modular sensor system that combine…

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Vinaik Chhetri, Krishna Upadhyay, A. B. Siddique, Umar Farooq
https://arxiv.org/abs/2506.10785

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Artificial Intelligence (AI)-powered features have rapidly proliferated across mobile apps in various domains, including productivity, education, entertainment, and creativity. However, how users perceive, evaluate, and critique these AI features remains largely unexplored, primarily due to the overwhelming volume of user feedback. In this work, we present the first comprehensive, large-scale study of user feedback on AI-powered mobile apps, leveraging a curated dataset of 292 AI-driven apps ac…

Electrification is still marginal in the Netherlands. Dutch electricity consumption in the first half of 2025 was almost exactly the same as a decade ago, in the first half of 2015 ( 0.3%).
Efficiency gains compensated for the modest shares of electric cars and heat pumps that did enter the scene.
Source:

Meer elektriciteit uit fossiele bronnen
Nederland produceerde in het eerste halfjaar van 2025 64 miljard kWh elektriciteit. Dit is 7 procent meer dan in het eerste halfjaar van 2024. Met name de productie uit fossiele bronnen steeg, vooral uit kolen. De productie uit hernieuwbare bronnen was lager, vooral uit windenergie. De productie uit zonne-energie piekte in het tweede kwartaal. Het verbruik van elektriciteit bleef gelijk. Dit meldt het Centraal Bureau voor de Statistiek (CBS) op basis van voorlopige cijfers.

LLM-as-a-Supervisor: Mistaken Therapeutic Behaviors Trigger Targeted Supervisory Feedback
Chen Xu, Zhenyu Lv, Tian Lan, Xianyang Wang, Luyao Ji, Leyang Cui, Minqiang Yang, Jian Shen, Qunxi Dong, Xiuling Liu, Juan Wang, Bin Hu
https://arxiv.org/abs/2508.09042

LLM-as-a-Supervisor: Mistaken Therapeutic Behaviors Trigger Targeted Supervisory Feedback
Although large language models (LLMs) hold significant promise in psychotherapy, their direct application in patient-facing scenarios raises ethical and safety concerns. Therefore, this work shifts towards developing an LLM as a supervisor to train real therapists. In addition to the privacy of clinical therapist training data, a fundamental contradiction complicates the training of therapeutic behaviors: clear feedback standards are necessary to ensure a controlled training system, yet there i…

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Sensory robustness through top-down feedback and neural stochasticity in recurrent vision models
Antonino Greco, Marco D'Alessandro, Karl J. Friston, Giovanni Pezzulo, Markus Siegel
https://arxiv.org/abs/2508.07115

Sensory robustness through top-down feedback and neural stochasticity in recurrent vision models
Biological systems leverage top-down feedback for visual processing, yet most artificial vision models succeed in image classification using purely feedforward or recurrent architectures, calling into question the functional significance of descending cortical pathways. Here, we trained convolutional recurrent neural networks (ConvRNN) on image classification in the presence or absence of top-down feedback projections to elucidate the specific computational contributions of those feedback pathw…

Dean of LLM Tutors: Exploring Comprehensive and Automated Evaluation of LLM-generated Educational Feedback via LLM Feedback Evaluators
Keyang Qian, Yixin Cheng, Rui Guan, Wei Dai, Flora Jin, Kaixun Yang, Sadia Nawaz, Zachari Swiecki, Guanliang Chen, Lixiang Yan, Dragan Ga\v{s}evi\'c
https://arxiv.org/abs/2508.05952

Dean of LLM Tutors: Exploring Comprehensive and Automated Evaluation of LLM-generated Educational Feedback via LLM Feedback Evaluators
The use of LLM tutors to provide automated educational feedback to students on student assignment submissions has received much attention in the AI in Education field. However, the stochastic nature and tendency for hallucinations in LLMs can undermine both quality of learning experience and adherence to ethical standards. To address this concern, we propose a method that uses LLM feedback evaluators (DeanLLMs) to automatically and comprehensively evaluate feedback generated by LLM tutor for su…