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Large Language Models (LLMs) struggle with complex reasoning due to limited diversity and inefficient search. We propose Soft Reasoning, an embedding-based search framework that optimises the embedding of the first token to guide…

Computation and Language · Computer Science 2025-09-16 Qinglin Zhu , Runcong Zhao , Hanqi Yan , Yulan He , Yudong Chen , Lin Gui

An efficient numerical method is developed using the matrix product formalism for computing the properties at finite energy densities in one-dimensional (1D) many-body localized (MBL) systems. Arguing that any efficient (possibly quantum)…

Disordered Systems and Neural Networks · Physics 2015-08-20 Yichen Huang

We consider a generic one dimensional spin system of length $ L $, arbitrarily large, with strictly local interactions, for example nearest neighbor, and prove that the dynamical $ \alpha $-R\'enyi entropies, $ 0 < \alpha \le 1 $, of an…

Quantum Physics · Physics 2025-08-25 Daniele Toniolo , Sougato Bose

Long-context models(LCMs) have shown great potential in processing long input sequences(even more than 100M tokens) conveniently and effectively. With significant progress, recent research has pointed out that LCMs can accurately locate…

Computation and Language · Computer Science 2024-10-25 Zecheng Tang , Zechen Sun , Juntao Li , Qiaoming Zhu , Min Zhang

The dynamics of quantum systems strongly depends on the local structure of the Hamiltonian. For short-range interacting systems, the well-known Lieb-Robinson bound defines the effective light cone with an exponentially small error with…

Quantum Physics · Physics 2016-05-31 Tomotaka Kuwahara

Locally decodable codes (LDCs) are error-correcting codes $C : \Sigma^k \to \Sigma^n$ that admit a local decoding algorithm that recovers each individual bit of the message by querying only a few bits from a noisy codeword. An important…

Computational Complexity · Computer Science 2020-09-17 Vahid R. Asadi , Igor Shinkar

Non-equilibrium dynamics of many-body quantum systems under the effect of measurement protocols is attracting an increasing amount of attention. It has been recently revealed that measurements may induce an abrupt change in the scaling-law…

Statistical Mechanics · Physics 2022-03-23 Michele Coppola , Emanuele Tirrito , Dragi Karevski , Mario Collura

Neural compression has brought tremendous progress in designing lossy compressors with good rate-distortion (RD) performance at low complexity. Thus far, neural compression design involves transforming the source to a latent vector, which…

Information Theory · Computer Science 2025-07-15 Eric Lei , Hamed Hassani , Shirin Saeedi Bidokhti

The fate of Many-Body Localization (MBL) in the thermodynamic limit remains elusive, partly because numerical studies suffer from unexplained finite-size effects. We introduce and numerically study the charge transport capacity (CTC) -- a…

Disordered Systems and Neural Networks · Physics 2026-04-22 Jessica Kaijia Jiang , Federica Maria Surace , Olexei I. Motrunich

We introduce the numerical linked cluster (NLC) expansion as a controlled numerical tool for the study of the many-body localization (MBL) transition in a disordered system with continuous non-perturbative disorder. Our approach works…

Strongly Correlated Electrons · Physics 2015-10-29 Trithep Devakul , Rajiv R. P. Singh

We study the influence of conservation laws on entanglement growth. Focusing on systems with U(1) symmetry, i.e., conservation of charge or magnetization, that exhibits diffusive dynamics, we theoretically predict the growth of…

Strongly Correlated Electrons · Physics 2020-06-25 Marko Znidaric

Test-time scaling has enabled Large Language Models (LLMs) to tackle complex reasoning, yet the limitations of current Chain-of-Thought (CoT) evaluation obscures whether performance gains stem from genuine reasoning or mere verbosity. To…

Artificial Intelligence · Computer Science 2026-01-08 Zhizhang Fu , Yuancheng Gu , Chenkai Hu , Hanmeng Liu , Yue Zhang

The mean and the variance of the logarithm of the conductance ($ln g$) in the localized regime in the one-dimensional Anderson model are calculated analytically for weak disorder, starting from the recursion relations for the complex…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 J. Heinrichs

Large reasoning models (LRMs) excel on complex problems but face a critical barrier to efficiency: reinforcement learning (RL) training requires long rollouts for outcome-based rewards, where autoregressive decoding dominates time and…

Machine Learning · Computer Science 2026-02-20 Zeliang Zhang , Xiaodong Liu , Hao Cheng , Hao Sun , Chenliang Xu , Jianfeng Gao

Evaluating the abilities of large language models (LLMs) for tasks that require long-term memory and thus long-context reasoning, for example in conversational settings, is hampered by the existing benchmarks, which often lack narrative…

Computation and Language · Computer Science 2026-02-24 Mohammad Tavakoli , Alireza Salemi , Carrie Ye , Mohamed Abdalla , Hamed Zamani , J Ross Mitchell

Tokenization is the first - and often underappreciated - layer of computation in language models. While Chain-of-Thought (CoT) prompting enables transformer models to approximate recurrent computation by externalizing intermediate steps, we…

Computation and Language · Computer Science 2025-05-21 Xiang Zhang , Juntai Cao , Jiaqi Wei , Yiwei Xu , Chenyu You

We prove novel speed limits on the growth of entanglement, equal-time correlators, and spacelike Wilson loops in spatially uniform time-evolving states in strongly coupled CFTs with holographic duals. These bounds can also be viewed as…

High Energy Physics - Theory · Physics 2023-02-10 Åsmund Folkestad , Aditya Dhumuntarao

Large Language Models (LLMs) have demonstrated remarkable proficiency in language comprehension and generation; however, their widespread adoption is constrained by substantial bandwidth and computational demands. While pruning and low-rank…

Computation and Language · Computer Science 2025-10-31 Zeliang Zong , Kai Zhang , Zheyang Li , Wenming Tan , Ye Ren , Yiyan Zhai , Jilin Hu

By tightening the conventional Lieb-Robinson bounds to better handle systems which lack translation invariance, we determine the extent to which "weak links" suppress operator growth in disordered one-dimensional spin chains. In particular,…

Disordered Systems and Neural Networks · Physics 2024-04-23 Christopher L. Baldwin , Adam Ehrenberg , Andrew Y. Guo , Alexey V. Gorshkov

An important and incompletely answered question is whether a closed quantum system of many interacting particles can be localized by disorder. The time evolution of simple (unentangled) initial states is studied numerically for a system of…

Strongly Correlated Electrons · Physics 2012-07-11 Jens H. Bardarson , Frank Pollmann , Joel E. Moore