Tootfinder

Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Zhanxin Hao, Jie Cao, Ruimiao Li, Jifan Yu, Zhiyuan Liu, Yu Zhang
https://arxiv.org/abs/2506.02993

Mapping Student-AI Interaction Dynamics in Multi-Agent Learning Environments: Supporting Personalised Learning and Reducing Performance Gaps
Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interactive learning. Yet, student-AI interaction patterns and their pedagogical implications remain unclear. This study explores how university students engaged with multiple AI agents, and how these interactions influenced cognitive outcomes (learning gains) and non-cognitive factors (motivation, technology acceptance). Based on MAIC, an online learning p…

This https://arxiv.org/abs/2506.00140 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Balancing Profit and Fairness in Risk-Based Pricing Markets
Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through a learned, interpretable tax schedule. First, we provide a formal proposition that bounding each firm's \emph{local} demographic gap implicitly bounds the \emph{global} opt-out disparity, motivating firm-level penalties. Building on this insight we introduce …

Nonlinear Causal Discovery for Grouped Data
Konstantin G\"obler, Tobias Windisch, Mathias Drton
https://arxiv.org/abs/2506.05120 https://

Nonlinear Causal Discovery for Grouped Data
Inferring cause-effect relationships from observational data has gained significant attention in recent years, but most methods are limited to scalar random variables. In many important domains, including neuroscience, psychology, social science, and industrial manufacturing, the causal units of interest are groups of variables rather than individual scalar measurements. Motivated by these applications, we extend nonlinear additive noise models to handle random vectors, establishing a two-step …

Autonomous Behavior and Whole-Brain Dynamics Emerge in Embodied Zebrafish Agents with Model-based Intrinsic Motivation
Reece Keller, Alyn Tornell, Felix Pei, Xaq Pitkow, Leo Kozachkov, Aran Nayebi
https://arxiv.org/abs/2506.00138

Autonomous Behavior and Whole-Brain Dynamics Emerge in Embodied Zebrafish Agents with Model-based Intrinsic Motivation
Autonomy is a hallmark of animal intelligence, enabling adaptive and intelligent behavior in complex environments without relying on external reward or task structure. Existing reinforcement learning approaches to exploration in sparse reward and reward-free environments, including class of methods known as intrinsic motivation, exhibit inconsistent exploration patterns and thus fail to produce robust autonomous behaviors observed in animals. Moreover, systems neuroscience has largely overlooke…

This https://arxiv.org/abs/2405.14942 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Mapping 1+1-dimensional black hole thermodynamics to finite volume effects
Both black hole thermodynamics and finite volume effects in quantum field theory violate the null energy condition. Motivated by this, we compare thermodynamic features between two $1+1$-dimensional systems: (i) a scalar field confined to a periodic spatial interval of length $a$ and tunneling between two degenerate vacua; (ii) a dilatonic black hole at temperature $T$ in the presence of matter fields. If we identify $a\propto T^{-1}$, we find similar thermodynamic behaviour, which suggests som…

This https://arxiv.org/abs/2501.08783 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Form factors of light pseudoscalar mesons from the perturbative QCD approach
We study the electromagnetic and meson-photon transition form factors (TFF) of light pseudoscalar mesons from the perturbative QCD (pQCD) approach. To comprehensively account for both the longitudinal and transverse nonperturbative dynamics of hadronic constituents, we incorpoarate intrinsic transverse momentum distributions (iTMDs) alongside the conventional light-cone distribution amplitudes (LCDAs). The main motivations of this work are the disjointedness of electromagnetic form factors betw…

This https://arxiv.org/abs/2503.03076 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Non-Affine Extensions of the Raychaudhuri Equation in the K-essence Framework
We present a new avenue of the Raychaudhuri Equation (RE) by introducing a non-affine parametrization within the k-essence framework. This modification accounts for non-geodesic flow curves, leading to emergent repulsive effects in cosmic evolution. Using a DBI-type k-essence Lagrangian, we derive a modified RE and demonstrate its ability to address the Hubble tension while predicting a natural emergence of a dynamical dark energy equation of state. Our Bayesian analysis, constrained by cosmolo…

This https://arxiv.org/abs/2312.13658 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Sample-based nonlinear detectability for discrete-time systems
This paper introduces two sample-based formulations of incremental input/output-to-state stability (i-IOSS), a suitable detectability notion for general nonlinear systems. In this work we consider the case of limited output information, i.e., measurements are only infrequently and/or irregularly available. The output-dependent term of the sample-based i-IOSS bound is properly modified to yield a characterization for detectability in presence of incomplete output sequences. We provide both a non…

Region-of-Interest-Guided Deep Joint Source-Channel Coding for Image Transmission
Hansung Choi, Daewon Seo
https://arxiv.org/abs/2506.01269 https://…

Region-of-Interest-Guided Deep Joint Source-Channel Coding for Image Transmission
Deep joint source-channel coding (deepJSCC) and semantic communication have shown promising improvements in communication performance over wireless networks. However, current approaches primarily focus on enhancing average performance metrics, such as overall image reconstruction quality or task accuracy, which may not fully align with users' actual experience -- often driven by the quality of specific regions of interest (ROI). Motivated by this, we propose ROI-guided joint source-channel codi…

Modified wave operators for the defocusing cubic nonlinear Schr\"odinger equation in one space dimension with large scattering data
Masaki Kawamoto, Haruya Mizutani
https://arxiv.org/abs/2506.01871

Modified wave operators for the defocusing cubic nonlinear Schrödinger equation in one space dimension with large scattering data
In the present paper, we construct modified wave operators for the defocusing cubic nonlinear Schrödinger equation (NLS) in one space dimension without size restriction on scattering data. In the proof, we introduce a new formulation of the problem based on the linearization of the NLS around a prescribed asymptotic profile. For the linearized equation which is a system of Schrödinger equations with non-symmetric, time-dependent long-range potentials, we show a modified energy identity, as we…