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Pre-trained large language models based on Transformers have demonstrated remarkable in-context learning (ICL) abilities. With just a few demonstration examples, the models can implement new tasks without any parameter updates. However, it…

Machine Learning · Computer Science 2024-11-04 Ruifeng Ren , Yong Liu

A new Muon-to-Central-Trigger Processor Interface (MUCTPI) was built as part of the upgrade of the ATLAS Level-1 trigger system for the next Run of the Large Hadron Collider at CERN. The MUCTPI has 208 high-speed optical serial links for…

Typically, even low-level operating system concepts, such as resource sharing strategies and predictability measures, are evaluated with Linux on PC hardware. This leaves a large gap to real industrial applications. Hence, the direct…

Operating Systems · Computer Science 2020-09-02 Oliver Horst , Uwe Baumgarten

This article describes a volumetric approach for procedural shape modeling and a new Procedural Shape Modeling Language (PSML) that facilitates the specification of these models. PSML provides programmers the ability to describe shapes in…

Graphics · Computer Science 2021-03-23 Andrew Willis , Prashant Ganesh , Kyle Volle , Jincheng Zhang , Kevin Brink

Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of…

Artificial Intelligence · Computer Science 2008-11-03 Marko A. Rodriguez , Jennifer H. Watkins , Johan Bollen , Carlos Gershenson

Resonance-assisted tunneling is investigated within the framework of one-dimensional integrable systems. We present a systematic recipe, based on Hamiltonian normal forms, to construct one-dimensional integrable models that exhibit…

Quantum Physics · Physics 2013-11-13 Jérémy Le Deunff , Amaury Mouchet , Peter Schlagheck

Large Language models (LLMs) have achieved encouraging results in tabular data generation. However, existing approaches require fine-tuning, which is computationally expensive. This paper explores an alternative: prompting a fixed LLM with…

Machine Learning · Computer Science 2025-02-25 Liancheng Fang , Aiwei Liu , Hengrui Zhang , Henry Peng Zou , Weizhi Zhang , Philip S. Yu

This works considers challenges of building and usage a formal knowledge base (model), which unites the ATT&CK, CAPEC, CWE, CVE security enumerations. The proposed model can be used to learn relations between attack techniques, attack…

Cryptography and Security · Computer Science 2021-12-09 Andrei Brazhuk

Serving large language models (LLMs) in production can incur substantial costs, which has prompted recent advances in inference system optimizations. Today, these systems are evaluated against conventional latency and throughput metrics…

A proper parametrization of state transition matrices of linear state-space models (SSMs) followed by standard nonlinearities enables them to efficiently learn representations from sequential data, establishing the state-of-the-art on a…

Machine Learning · Computer Science 2022-09-28 Ramin Hasani , Mathias Lechner , Tsun-Hsuan Wang , Makram Chahine , Alexander Amini , Daniela Rus

Motivated by the challenge presented by non-Markovian objectives in reinforcement learning (RL), we present a novel framework to track and represent the progress of autonomous agents through complex, multi-stage tasks. Given a specification…

Machine Learning · Computer Science 2026-04-21 Noel Brindise , Cedric Langbort , Melkior Ornik

This paper introduces a methodology for identifying and simulating financial and economic systems using stochastically structured reservoir computers (SSRCs). The framework combines structure-preserving embeddings with graph-informed…

Optimization and Control · Mathematics 2025-11-20 Lendy Banegas , Fredy Vides

In this paper, we present Real-Time Analog Monitoring Tool (RTAMT), a tool for quantitative monitoring of Signal Temporal Logic (STL) specifications. The library implements a flexible architecture that supports: (1) various environments…

Logic in Computer Science · Computer Science 2025-02-03 Tomoya Yamaguchi , Bardh Hoxha , Dejan Nickovic

Requirements engineering plays a critical role in developing software systems. One of the most difficult tasks in this process is identifying functional requirements. A critical problem in many projects is missing requirements until late in…

Software Engineering · Computer Science 2020-04-02 Sabah Al-Fedaghi

As tools for designing multiple processor systems-on-chips (MPSoCs) continue to evolve to meet the demands of developers, there exist systematic gaps that must be bridged to provide a more cohesive hardware/software development environment.…

Software Engineering · Computer Science 2014-08-21 Sam Skalicky , Andrew G. Schmidt , Matthew French

The numerical simulation of multiple scattering in dense ensembles is the mostly adopted solution to predict their complex optical response. While the scalar and vectorial light mediated interactions are accurately taken into account, the…

Topology optimization enables the design of highly efficient and complex structures, but conventional iterative methods, such as SIMP-based approaches, often suffer from high computational costs and sensitivity to initial conditions.…

Computational Engineering, Finance, and Science · Computer Science 2025-09-18 Aaron Lutheran , Srijan Das , Alireza Tabarraei

Information technology system (ITS), informally, consists of hardware and software infrastructure (e.g., workstations, servers, laptops, installed software packages, databases, LANs, firewalls, etc.), along with physical and logical…

Cryptography and Security · Computer Science 2022-02-01 Ivan Kovačević , Stjepan Groš , Ante Đerek

We describe the architecture evolution of the highly-parallel dedicated processor FTK, which is driven by the simulation of LHC events at high luminosity (1034 cm-2 s-1). FTK is able to provide precise on-line track reconstruction for…

This article proposes a methodology to model and simulate complex systems, based on IRM4MLS, a generic agent-based meta-model able to deal with multi-level systems. This methodology permits the engineering of dynamic multi-level agent-based…

Multiagent Systems · Computer Science 2013-11-21 Jean-Baptiste Soyez , Gildas Morvan , Daniel Dupont , Rochdi Merzouki
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