Tootfinder

AI, Expert or Peer? -- Examining the Impact of Perceived Feedback Source on Pre-Service Teachers Feedback Perception and Uptake
Lucas Jasper Jacobsen, Ute Mertens, Thorben Jansen, Kira Elena Weber
https://arxiv.org/abs/2507.16013

AI, Expert or Peer? -- Examining the Impact of Perceived Feedback Source on Pre-Service Teachers Feedback Perception and Uptake
Feedback plays a central role in learning, yet pre-service teachers' engagement with feedback depends not only on its quality but also on their perception of the feedback content and source. Large Language Models (LLMs) are increasingly used to provide educational feedback; however, negative perceptions may limit their practical use, and little is known about how pre-service teachers' perceptions and behavioral responses differ by feedback source. This study investigates how the perceived sourc…

Benefiting from Negative yet Informative Feedback by Contrasting Opposing Sequential Patterns
Veronika Ivanova, Evgeny Frolov, Alexey Vasilev
https://arxiv.org/abs/2508.14786 ht…

Benefiting from Negative yet Informative Feedback by Contrasting Opposing Sequential Patterns
We consider the task of learning from both positive and negative feedback in a sequential recommendation scenario, as both types of feedback are often present in user interactions. Meanwhile, conventional sequential learning models usually focus on considering and predicting positive interactions, ignoring that reducing items with negative feedback in recommendations improves user satisfaction with the service. Moreover, the negative feedback can potentially provide a useful signal for more acc…

Roles of SN and AGN Feedback in Shaping the Baryonic Content in a Wide Range of Dark Matter Halo Mass
Emanuele Contini, Chanjo Seo, Jinsu Rhee, Jeon Seyoung, Sukyoung K. Yi
https://arxiv.org/abs/2507.10673

Roles of SN and AGN Feedback in Shaping the Baryonic Content in a Wide Range of Dark Matter Halo Mass
We build upon FEGA25 (Contini et al 2025), a previously introduced semi-analytic model for galaxy formation and evolution, focusing on its enhanced treatment of supernova and active galactic nucleus feedback mechanisms. In addition to the traditional AGN feedback modes, negative (suppressing cooling), and the new positive mode (triggering star formation), we introduce two implementations of a third mode: the ejection of hot gas beyond the virial radius, AGNeject1 and AGNeject2. This component a…

Replaced article(s) found for q-bio.MN. https://arxiv.org/list/q-bio.MN/new
[1/1]:
- Negative feedback and oscillations in a model for mRNA translation
Aliza Ehrman, Thomas Kriecherbauer, Lars Gruene, Michael Margaliot

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
Zeqiang Zhang, Fabian Wurzberger, Gerrit Schmid, Sebastian Gottwald, Daniel A. Braun
https://arxiv.org/abs/2509.03206

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
Reinforcement learning faces significant challenges when applied to tasks characterized by sparse reward structures. Although imitation learning, within the domain of supervised learning, offers faster convergence, it relies heavily on human-generated demonstrations. Recently, Goal-Conditioned Supervised Learning (GCSL) has emerged as a potential solution by enabling self-imitation learning for autonomous systems. By strategically relabelling goals, agents can derive policy insights from their …

Spiking control systems for soft robotics: a rhythmic case study in a soft robotic crawler
Juncal Arbelaiz, Alessio Franci, Naomi Ehrich Leonard, Rodolphe Sepulchre, Bassam Bamieh
https://arxiv.org/abs/2509.02968

Spiking control systems for soft robotics: a rhythmic case study in a soft robotic crawler
Inspired by spiking neural feedback, we propose a spiking controller for efficient locomotion in a soft robotic crawler. Its bistability, akin to neural fast positive feedback, combined with a sensorimotor slow negative feedback loop, generates rhythmic spiking. The closed-loop system is robust through the quantized actuation, and negative feedback ensures efficient locomotion with minimal external tuning. We prove that peristaltic waves arise from a supercritical Hopf bifurcation controlled by…

Turbulent wind thrust control to reduce pitch motion of floating wind platforms with improved rotor operation
Yi Zhang, Peter Stansby, David Apsley, Hannah Mullings
https://arxiv.org/abs/2509.11707

Turbulent wind thrust control to reduce pitch motion of floating wind platforms with improved rotor operation
For the dynamic analysis of floating offshore wind turbines (FOWTs) in realistic operating environment, this paper develops a coupled aero-hydro-mooring-servo model applicable to turbulent wind and irregular sea states with high computational efficiency. A modified rotor control strategy with platform motion feedback is proposed with a novel gain-scheduling technique to mitigate the negative damping effect on platform motions and decouple the rotor dynamics from the platform dynamics for better…

Graphs With Polarities
John C. Baez, Adittya Chaudhuri
https://arxiv.org/abs/2506.23375 https://arxiv.org/pdf/2506.23375

Graphs With Polarities
In fields ranging from business to systems biology, directed graphs with edges labeled by signs are used to model systems in a simple way: the nodes represent entities of some sort, and an edge indicates that one entity directly affects another either positively or negatively. Multiplying the signs along a directed path of edges lets us determine indirect positive or negative effects, and if the path is a loop we call this a positive or negative feedback loop. Here we generalize this to graphs …

Organic Electrochemical Neurons: Nonlinear Tools for Complex Dynamics
Gonzalo Rivera-Sierra, Roberto Fenollosa, Juan Bisquert
https://arxiv.org/abs/2508.00663 https://

Organic Electrochemical Neurons: Nonlinear Tools for Complex Dynamics
Hybrid oscillator architectures that combine feedback oscillators with self-sustained negative resistance oscillators have emerged as a promising platform for artificial neuron design. In this work, we introduce a modeling and analysis framework for amplifier-assisted organic electrochemical neurons, leveraging nonlinear dynamical systems theory. By formulating the system as coupled differential equations describing membrane voltage and internal state variables, we identify the conditions for s…