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As large language models (LLMs) scale, their inference incurs substantial computational resources, exposing them to energy-latency attacks, where crafted prompts induce high energy and latency cost. Existing attack methods aim to prolong…

Cryptography and Security · Computer Science 2025-11-12 Xingyu Li , Xiaolei Liu , Cheng Liu , Yixiao Xu , Kangyi Ding , Bangzhou Xin , Jia-Li Yin

We consider a branching model of triggered seismicity, the ETAS (epidemic-type aftershock sequence) model which assumes that each earthquake can trigger other earthquakes (``aftershocks''). An aftershock sequence results in this model from…

Geophysics · Physics 2009-11-10 A. Saichev , D. Sornette

Single-step retrieval-augmented generation (RAG) provides an efficient way to incorporate external information for simple question answering tasks but struggles with complex questions. Agentic RAG extends this paradigm by replacing…

Computation and Language · Computer Science 2026-05-08 Yijia Zheng , Marcel Worring

The long-time dynamics of the 1D contact process suddenly brought out of an uncorrelated initial state is studied through a light-cone transfer-matrix renormalisation group approach. At criticality, the system undergoes ageing which is…

Statistical Mechanics · Physics 2007-05-23 Tilman Enss , Malte Henkel , Alan Picone , Ulrich Schollwöck

Using the Metropolis algorithm, we simulate the relaxation process of the three-dimensional kinetic Ising model. Starting from a random initial configuration, we first present the average equilibration time across the entire phase boundary.…

Statistical Mechanics · Physics 2025-01-27 Xiaobing Li , Ranran Guo , Mingmei Xu , Jinghua Fu , Lizhu Chen , Yu Zhou , Yuanfang Wu

As well known, the generalized Langevin equation with a memory kernel decreasing at large times as an inverse power law of time describes the motion of an anomalously diffusing particle. Here, we focus attention on some new aspects of the…

Statistical Mechanics · Physics 2011-05-27 Noëlle Pottier

Linear Response theory aims to predict how added forcing alters the statistical properties of an unforced system. These kinds of questions have been studied predominantly for autonomous dynamical systems, yet many systems in the physical,…

Dynamical Systems · Mathematics 2026-04-07 Stefano Galatolo , Valerio Lucarini

This paper presents AlphaOne ($\alpha$1), a universal framework for modulating reasoning progress in large reasoning models (LRMs) at test time. $\alpha$1 first introduces $\alpha$ moment, which represents the scaled thinking phase with a…

Computation and Language · Computer Science 2025-06-02 Junyu Zhang , Runpei Dong , Han Wang , Xuying Ning , Haoran Geng , Peihao Li , Xialin He , Yutong Bai , Jitendra Malik , Saurabh Gupta , Huan Zhang

Adaptive control of Euler-Lagrange systems is challenging when friction is governed by a finite-horizon internal state that is not directly observable from joint measurements. In this setting, the measured closed-loop state is no longer…

Machine Learning · Computer Science 2026-05-11 Giansalvo Cirrincione , Adriano Fagiolini

Standard chain-of-thought reasoning generates a solution in a single forward pass, committing irrevocably to each token and lacking a mechanism to recover from early errors. We introduce Inference-Time Rethinking, a generative framework…

Computation and Language · Computer Science 2026-02-09 Deqian Kong , Minglu Zhao , Aoyang Qin , Bo Pang , Chenxin Tao , David Hartmann , Edouardo Honig , Dehong Xu , Amit Kumar , Matt Sarte , Chuan Li , Jianwen Xie , Ying Nian Wu

Consistency and predictability of brain functionalities depend on reproducible activity of a single neuron. We identify a reproducible non-chaotic neuronal phase where deviations between concave response latency profiles of a single neuron…

Neurons and Cognition · Quantitative Biology 2014-05-27 Hagar Marmari , Roni Vardi , Ido Kanter

Intermediate token generation (ITG), where a model produces output before the solution, has been proposed as a method to improve the performance of language models on reasoning tasks. While these reasoning traces or Chain of Thoughts (CoTs)…

Artificial Intelligence · Computer Science 2025-09-10 Vardhan Palod , Karthik Valmeekam , Kaya Stechly , Subbarao Kambhampati

Retrieval-Augmented Generation (RAG) enhances the reasoning ability of Large Language Models (LLMs) by dynamically integrating external knowledge, thereby mitigating hallucinations and strengthening contextual grounding for structured data…

Artificial Intelligence · Computer Science 2026-02-24 Sen Zhao , Lincheng Zhou , Yue Chen , Ding Zou

Spike-frequency adaptation (SFA) is a fundamental neuronal mechanism taking into account the fatigue due to spike emissions and the consequent reduction of the firing activity. We have studied the effect of this adaptation mechanism on the…

Disordered Systems and Neural Networks · Physics 2023-03-08 Alberto Ferrara , David Angulo-Garcia , Alessandro Torcini , Simona Olmi

We study in details the dynamics of the one dimensional symmetric trap model, via a real-space renormalization procedure which becomes exact in the limit of zero temperature. In this limit, the diffusion front in each sample consists in two…

Condensed Matter · Physics 2009-11-10 Cecile Monthus

State-of-the-art language generation models can degenerate when applied to open-ended generation problems such as text completion, story generation, or dialog modeling. This degeneration usually shows up in the form of incoherence, lack of…

Computation and Language · Computer Science 2023-02-15 Kushal Arora , Timothy J. O'Donnell , Doina Precup , Jason Weston , Jackie C. K. Cheung

Retrieval-augmented generation has gained significant attention due to its ability to integrate relevant external knowledge, enhancing the accuracy and reliability of the LLMs' responses. Most of the existing methods apply a dynamic…

Computation and Language · Computer Science 2025-01-13 Liang Xiao , Wen Dai , Shuai Chen , Bin Qin , Chongyang Shi , Haopeng Jing , Tianyu Guo

Criticality and symmetry, studied by the renormalization groups, lie at the heart of modern physics theories of matters and complex systems. However, surveying these properties with massive experimental data is bottlenecked by the…

Statistical Mechanics · Physics 2024-01-30 Yang Tian , Yizhou Xu , Pei Sun

Contrary to common belief, as the time since the last earthquake in a certain region increases, the risk of occurrence of another earthquake diminishes. As a consequence, the expected waiting time to the next event increases with the…

Condensed Matter · Physics 2009-11-10 Alvaro Corral

In the reaction-diffusion process $A+B \to \varnothing$ on random scale-free (SF) networks with the degree exponent $\gamma$, the particle density decays with time in a power law with an exponent $\alpha$ when initial densities of each…

Disordered Systems and Neural Networks · Physics 2015-05-13 C. -K. Yun , B. Kahng , D. Kim