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We study the linear response to an external perturbation of a renewal process, in an aging condition that, with no perturbation, would yield super-diffusion. We use the phenomenological approach to the linear response adopted in earlier…

Statistical Mechanics · Physics 2007-05-23 Paolo Allegrini , Gianluca Ascolani , Mauro Bologna , Paolo Grigolini

The scalability of large language models for long-context reasoning is severely constrained by the linear growth of their Transformer key-value cache, which incurs significant memory and computational costs. We posit that as a model…

Computation and Language · Computer Science 2025-12-30 Giovanni Monea , Yair Feldman , Shankar Padmanabhan , Kianté Brantley , Yoav Artzi

Large language models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet exhibit critical limitations in knowledge-intensive tasks, often generating hallucinations when faced with questions requiring…

Computation and Language · Computer Science 2026-01-08 Yilin Xiao , Chuang Zhou , Yujing Zhang , Qinggang Zhang , Su Dong , Shengyuan Chen , Chang Yang , Xiao Huang

Consider first a memoryless population model described by the usual branching process with a given mean reproduction matrix on a finite space of types. Motivated by the consequences of atavism in Evolutionary Biology, we are interested in a…

Probability · Mathematics 2025-01-03 Jean Bertoin

Many driven systems alternate between bursts of activity and quiescence and can become trapped in an absorbing state, such as complete inactivity in reaction-diffusion processes or extinction in predator-prey dynamics. It is generally…

Statistical Mechanics · Physics 2026-05-14 Kartik Chhajed , P. K. Mohanty

\emph{Resistive memories}, such as \emph{phase change memories} and \emph{resistive random access memories} have attracted significant attention in recent years due to their better scalability, speed, rewritability, and yet non-volatility.…

Information Theory · Computer Science 2021-09-22 Yeow Meng Chee , Michal Horovitz , Alexander Vardy , Van Khu Vu , Eitan Yaakobi

We observe non-monotonic aging and memory effects, two hallmarks of glassy dynamics, in two disordered mechanical systems: crumpled thin sheets and elastic foams. Under fixed compression, both systems exhibit monotonic non-exponential…

Soft Condensed Matter · Physics 2017-04-14 Yoav Lahini , Omer Gottesman , Ariel Amir , Shmuel M. Rubinstein

Traditional studies of memory for meaningful narratives focus on specific stories and their semantic structures but do not address common quantitative features of recall across different narratives. We introduce a statistical ensemble of…

Statistical Mechanics · Physics 2025-02-25 Weishun Zhong , Tankut Can , Antonis Georgiou , Ilya Shnayderman , Mikhail Katkov , Misha Tsodyks

We monitor the relaxation of internal stresses in a fractal colloidal gel on cessation of flow and find a weak power law decay, $\sigma_i \sim t^{-\alpha}$ over 5 decades of time where $\alpha \approx 0.07$. The system exhibits physical…

Soft Condensed Matter · Physics 2009-06-17 Ajay Singh Negi , Chinedum O. Osuji

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the…

Molecular Networks · Quantitative Biology 2018-02-26 Peter Csermely

Lifelong sequence generation (LSG), a problem in continual learning, aims to continually train a model on a sequence of generation tasks to learn constantly emerging new generation patterns while avoiding the forgetting of previous…

Computation and Language · Computer Science 2023-11-23 Chengwei Qin , Chen Chen , Shafiq Joty

A central challenge in continual learning is forgetting, the loss of performance on previously learned tasks induced by sequential adaptation to new ones. While forgetting has been extensively studied empirically, rigorous theoretical…

Machine Learning · Computer Science 2026-04-16 Zonghuan Xu , Xingjun Ma

We present a detailed discussion of the role played by memory, and the nature of self-induced shocks, in an evolutionary population competing for limited resources. Our study builds on a previously introduced multi-agent system [Phys. Rev.…

Statistical Mechanics · Physics 2009-11-10 Roland Kay , Neil F. Johnson

Recent studies of cortical neurons driven by fluctuating currents revealed cutoff frequencies for action potential encoding of several hundred Hz. Theoretical studies of biophysical neuron models have predicted a much lower cutoff frequency…

Neurons and Cognition · Quantitative Biology 2015-05-27 Wei Wei , Fred Wolf

Sinai's model of diffusion in one-dimension with random local bias is studied by a real space renormalization group which yields exact results at long times. The effects of an additional small uniform bias force are also studied. We obtain…

Condensed Matter · Physics 2009-10-31 Daniel S. Fisher , Pierre Le Doussal , Cecile Monthus

Large Reasoning Models (LRMs) demonstrate remarkable capabilities on complex tasks, exhibiting emergent, human-like thinking patterns. Despite their advances, we identify a fundamental limitation: current LRMs lack a dedicated meta-level…

Artificial Intelligence · Computer Science 2025-08-26 Haonan Dong , Haoran Ye , Wenhao Zhu , Kehan Jiang , Guojie Song

It has been proposed (Phys. Rev. E {\bf 71}, 026121 (2005)) that unlike the short range contact process, a long-range counterpart may lead to the existence a discontinuous phase transition in one dimension. Aiming at exploring such link,…

Statistical Mechanics · Physics 2013-06-14 Carlos E. Fiore , Mário J. de Oliveira

The time evolution of systems relaxing towards thermal equilibrium is examined near the critical temperature $T_c$, with special attention paid to the role of the initial value $m_i$ of the order parameter $\phi$. To this end, the…

Condensed Matter · Physics 2009-10-22 U. Ritschel , H. W. Diehl

Masked Diffusion Models (MDMs) significantly accelerate inference by trading off sequential determinism. However, the theoretical mechanisms governing generation order and the risks inherent in parallelization remain under-explored. In this…

Machine Learning · Computer Science 2026-02-03 Shaorong Zhang , Longxuan Yu , Rob Brekelmans , Luhan Tang , Salman Asif , Greg Ver Steeg

We introduce a family of synthetic languages with hierarchical structure -- generated by a broadcast process on trees -- for which the role of context length and reasoning in autoregressive generation can be analyzed precisely. At the heart…

Machine Learning · Computer Science 2026-05-14 Jason Gaitonde , Frederic Koehler , Elchanan Mossel , Joonhyung Shin , Allan Sly
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