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In this work, we demonstrate that affine mappings between residual streams of language models is a cheap way to effectively transfer represented features between models. We apply this technique to transfer the weights of Sparse Autoencoders…

Computation and Language · Computer Science 2025-11-04 Alan Chen , Jack Merullo , Alessandro Stolfo , Ellie Pavlick

Thompson Sampling is a principled method for balancing exploration and exploitation, but its real-world adoption faces computational challenges in large-scale or non-conjugate settings. While ensemble-based approaches offer partial…

Machine Learning · Computer Science 2025-10-29 Yingru Li , Jiawei Xu , Baoxiang Wang , Zhi-Quan Luo

In this paper, an energy-efficient cross-layer design framework is proposed for cooperative relaying networks, which takes into account the influence of spectrum utilization probability. Specifically, random arrival traffic is considered…

Signal Processing · Electrical Eng. & Systems 2020-02-28 Kunlun Wang , Qingqing Wu , Wen Chen , Yang Yang , Derrick Wing Kwan Ng

Many proteins in cells are capable of sensing and responding to piconewton scale forces, a regime in which conformational changes are small but significant for biological processes. In order to efficiently and effectively sample the…

Statistical Mechanics · Physics 2020-07-08 Michael J. Hartmann , Yuvraj Singh , Eric Vanden-Eijnden , Glen M. Hocky

Understanding the principles of protein folding is a cornerstone of computational biology, with implications for drug design, bioengineering, and the understanding of fundamental biological processes. Lattice protein folding models offer a…

Disordered Systems and Neural Networks · Physics 2025-08-08 Shoummo Ahsan Khandoker , Estelle M. Inack , Mohamed Hibat-Allah

Molecular simulations of the forced unfolding and refolding of biomolecules or molecular complexes allow to gain important kinetic, structural and thermodynamic information about the folding process and the underlying energy landscape. In…

Soft Condensed Matter · Physics 2021-05-26 Marco Oestereich , Jürgen Gauss , Gregor Diezemann

Advances in additive manufacturing (AM) enable new opportunities to design compact heat exchangers (cHEXs) by leveraging flexible geometries to improve energy and material efficiency. However, it is well known that reducing size in…

Computational Engineering, Finance, and Science · Computer Science 2025-12-17 Mehmet Basaran , Frederik Rogiers , Martine Baelmans , Maarten Blommaert

Replica exchange molecular dynamics (REMD) becomes more efficient as the frequency of swap between the temperatures is increased. Recently in [Plattner et al, J. Chem. Phys. 135, 134111 (2011)] a method was proposed to implement infinite…

Statistical Mechanics · Physics 2015-06-12 Jianfeng Lu , Eric Vanden-Eijnden

Understanding the impact of extractant functionalization in solvent extraction is essential to guide the development of better separations processes. Traditionally, computational extractant design uses electronic structure calculations to…

Chemical Physics · Physics 2023-12-15 Xiaoyu Wang , Michael J. Servis

Most recent state of the art architectures rely on combinations and variations of three approaches: convolutional, recurrent and self-attentive methods. Our work attempts in laying the basis for a new research direction for sequence…

Computer Vision and Pattern Recognition · Computer Science 2022-12-27 Jia Cheng Hu , Roberto Cavicchioli , Alessandro Capotondi

A polymer chain tethered to a surface may be compact or extended, adsorbed or desorbed, depending on interactions with the surface and the surrounding solvent. This leads to a rich phase diagram with a variety of transitions. To investigate…

Soft Condensed Matter · Physics 2009-11-13 Jutta Luettmer-Strathmann , Federica Rampf , Wolfgang Paul , Kurt Binder

Increasing the size of a Transformer does not always lead to enhanced performance. This phenomenon cannot be explained by the empirical scaling laws. Furthermore, the model's enhanced performance is closely associated with its memorization…

Machine Learning · Computer Science 2024-12-02 Xueyan Niu , Bo Bai , Lei Deng , Wei Han

Sampling from multimodal distributions is a central challenge in Bayesian inference and machine learning. In light of hardness results for sampling -- classical MCMC methods, even with tempering, can suffer from exponential mixing times --…

Machine Learning · Statistics 2025-12-23 Holden Lee , Matheau Santana-Gijzen

A novel approach to investigate the electron transport of cis- and trans-polyacetylene chains in the single-electron approximation is presented by using microwave emulation measurements and tight-binding calculations. In the emulation we…

Mesoscale and Nanoscale Physics · Physics 2016-11-14 Thomas Stegmann , John A. Franco-Villafañe , Yenni P. Ortiz , Ulrich Kuhl , Fabrice Mortessagne , Thomas H. Seligman

Mutual exclusion is one of the most commonly used techniques to handle contention in concurrent systems. Traditionally, mutual exclusion algorithms have been designed under the assumption that a process does not fail while…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-19 Sahil Dhoked , Neeraj Mittal

We consider the problem of constructing exact goodness-of-fit tests for discrete exponential family models. This classical problem remains practically unsolved for many types of structured or sparse data, as it rests on a computationally…

Machine Learning · Statistics 2025-12-31 Ivan Gvozdanović , Sonja Petrović

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez

The extension elasticity of rod-coil mutliblock copolymers is analyzed for two experimentally accessible situations. In the quenched case, when the architecture is fixed by the synthesis, the force law is distinguished by a sharp change in…

Soft Condensed Matter · Physics 2009-10-31 A. Buhot , A. Halperin

Sampling complex potential energies is one of the most pressing challenges of contemporary computational science. Inspired by recent efforts that use quantum effects and discretized Feynman's path integrals to overcome large barriers we…

Statistical Mechanics · Physics 2016-07-19 Marco Nava , Ferruccio Palazzesi , Claudio Perego , Michele Parrinello

Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and process or device technologies are increasingly important to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-02 Wilkie Olin-Ammentorp , Xingfu Wu , Andrew A. Chien