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Foundation models have demonstrated remarkable generalization, data efficiency, and robustness properties across various domains. In this paper, we explore the feasibility of foundation models for applications in the control domain. The…

Machine Learning · Computer Science 2024-12-18 Martin Ziegler , Andres Felipe Posada-Moreno , Friedrich Solowjow , Sebastian Trimpe

We propose a new sequential jet reconstruction algorithm for future lepton colliders at the energy frontier. The Valencia algorithm combines the natural distance criterion for lepton colliders with the greater robustness against backgrounds…

High Energy Physics - Experiment · Physics 2015-09-03 Marça Boronat , Ignacio Garcia , Marcel Vos

Continual learning (CL) is essential for Large Language Models (LLMs) to adapt to evolving real-world demands, yet they are susceptible to catastrophic forgetting (CF). While traditional CF solutions rely on expensive data rehearsal, recent…

Machine Learning · Computer Science 2025-02-18 Huanxuan Liao , Shizhu He , Yupu Hao , Jun Zhao , Kang Liu

Traditional foundation models are pre-trained on broad datasets to reduce the training resources (e.g., time, energy, labeled samples) needed for fine-tuning a wide range of downstream tasks. However, traditional foundation models struggle…

Machine Learning · Computer Science 2025-04-24 Majid Farhadloo , Arun Sharma , Mingzhou Yang , Bharat Jayaprakash , William Northrop , Shashi Shekhar

In recent years, the development of diffusion models has led to significant progress in image and video generation tasks, with pre-trained models like the Stable Diffusion series playing a crucial role. Inspired by model pruning which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Teng Hu , Jiangning Zhang , Ran Yi , Hongrui Huang , Yabiao Wang , Lizhuang Ma

Jet reconstruction remains a critical task in the analysis of data from HEP colliders. We describe in this paper a new, highly performant, Julia package for jet reconstruction, JetReconstruction.jl, which integrates into the growing…

High Energy Physics - Experiment · Physics 2025-12-02 Graeme Andrew Stewart. Sanmay Ganguly , Sattwamo Ghosh , Philippe Gras , Atell Krasnopolski

Fine-tuning has proven to be highly effective in adapting pre-trained models to perform better on new desired tasks with minimal data samples. Among the most widely used approaches are reparameterization methods, which update a target…

Machine Learning · Computer Science 2025-10-27 Aymane El Firdoussi , El Mahdi Chayti , Mohamed El Amine Seddik , Martin Jaggi

Algorithms based on the particle flow approach are becoming increasingly utilized in collider experiments due to their superior jet energy and missing energy resolution compared to the traditional calorimeter-based measurements. Such…

High Energy Physics - Experiment · Physics 2015-03-20 Andrey Elagin , Pavel Murat , Alexandre Pranko , Alexei Safonov

A search for new particles has been conducted using events with two high transverse momentum $\tau$ leptons that decay hadronically and at least two energetic jets. The analysis is performed using data from proton-proton collisions at…

High Energy Physics - Experiment · Physics 2019-04-03 CMS Collaboration

Searches for new physics in events with hadronic jets, missing transverse energy, and two leptons of which at least one is a hadronically decaying tau are presented. The result is based on a data sample corresponding to an integrated…

High Energy Physics - Experiment · Physics 2019-08-13 Matthias Edelhoff

A search for new particles has been conducted using events with two high transverse momentum (pt) tau leptons that decay hadronically, at least two high-pt jets, and missing transverse energy from the tau lepton decays. The analysis is…

High Energy Physics - Experiment · Physics 2017-03-21 CMS Collaboration

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC). Collision events produced at the LHC and represented as…

We refine the OrbNet model to accurately predict energy, forces, and other response properties for molecules using a graph neural-network architecture based on features from low-cost approximated quantum operators in the symmetry-adapted…

This study aims to improve the TauFinder reconstruction algorithm for the MAIA detector concept. Through this work, we seek to increase the reconstruction efficiency and identification of hadronically decaying tau leptons. Through our work,…

Instrumentation and Detectors · Physics 2026-01-13 Cyrus Kianian , Moses Glassman , Abdollah Mohammadi

Counterfactual explanations provide ways of achieving a favorable model outcome with minimum input perturbation. However, counterfactual explanations can also be leveraged to reconstruct the model by strategically training a surrogate model…

Machine Learning · Computer Science 2024-11-13 Pasan Dissanayake , Sanghamitra Dutta

Model merging is a technique that combines multiple large pretrained models into a single model with enhanced performance and broader task adaptability. It has gained popularity in large pretrained model development due to its ability to…

Machine Learning · Computer Science 2024-09-30 Yu Zhou , Xingyu Wu , Jibin Wu , Liang Feng , Kay Chen Tan

We present specialized Large Language Models for theoretical High-Energy Physics, obtained as 20 fine-tuned variants of the 8-billion parameter Llama-3.1 model. Each variant was trained on arXiv abstracts (through August 2024) from…

Computation and Language · Computer Science 2026-03-02 Paul Richmond , Prarit Agarwal , Borun Chowdhury , Vasilis Niarchos , Constantinos Papageorgakis

We give a pedagogical introduction to the rich phenomenology of hadronic tau decays. These decays provide a unique window into the interplay of electroweak and strong interactions at low energies, as they occur primarily via $W$ exchange…

High Energy Physics - Phenomenology · Physics 2025-05-01 Antonio Rodríguez-Sánchez

In this paper we study the performance in $e^+e^-$ collisions of classical $e^+e^-$ jet reconstruction algorithms, longitudinally invariant algorithms and the recently-proposed Valencia algorithm. The study includes a comparison of…

High Energy Physics - Experiment · Physics 2018-03-09 M. Boronat , J. Fuster , I. Garcia , Ph. Roloff , R. Simoniello , M. Vos

Finetuning pretrained models occurs in a low-dimensional subspace of the full parameter space. Prior work has focused on characterizing this optimization subspace, but largely ignored the complementary question: why do certain directions…

Machine Learning · Computer Science 2026-05-11 Junjie Yu , Yue Wang , Zihan Deng , Yan Zhu , Wenxiao Ma , Quanying Liu
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