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We present here a reverse engineering tool that can be used for information retrieval and anti-malware techniques. Our main contribution is the design and implementation of an instrumentation framework aimed at providing insight on the…

Cryptography and Security · Computer Science 2023-11-08 Paul Irofti

The detection of air-shower events via radio signals requires to develop a trigger algorithm for a clean discrimination between signal and background events in order to reduce the data stream coming from false triggers. In this contribution…

Instrumentation and Methods for Astrophysics · Physics 2018-12-11 Florian Führer , Tom Charnock , Anne Zilles , Matias Tueros

The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented on custom-designed electronics, and the High Level Trigger, a streamlined version of the CMS offline reconstruction software running on a…

Instrumentation and Detectors · Physics 2020-11-19 Thiago R. F. P. Tomei

In this paper, we propose a pragmatic approach to improve reproducibility of experimental analyses of traffic engineering (TE) algorithms, whose implementation, evaluation and comparison are currently hard to replicate. Our envisioned goal…

Networking and Internet Architecture · Computer Science 2017-10-25 Steven Gay , Pierre Schaus , Stefano Vissicchio

Automated feature engineering (AutoFE) is the process of automatically building and selecting new features that help improve downstream predictive performance. While traditional feature engineering requires significant domain expertise and…

Machine Learning · Computer Science 2025-02-28 Tom Overman , Diego Klabjan , Jean Utke

In software reverse engineering, decompilation is the process of recovering source code from binary files. Decompilers are used when it is necessary to understand or analyze software for which the source code is not available. Although…

Software Engineering · Computer Science 2021-02-25 Javier Escalada , Ted Scully , Francisco Ortin

Test-Time Scaling enhances the reasoning capabilities of Large Language Models by allocating additional inference compute to broaden the exploration of the solution space. However, existing search strategies typically treat rollouts as…

Computation and Language · Computer Science 2026-05-06 Xinglin Wang , Jiayi Shi , Shaoxiong Feng , Peiwen Yuan , Yiwei Li , Yueqi Zhang , Chuyi Tan , Ji Zhang , Boyuan Pan , Yao Hu , Kan Li

Cyber-physical systems come with increasingly complex architectures and failure modes, which complicates the task of obtaining accurate system reliability models. At the same time, with the emergence of the (industrial) Internet-of-Things,…

Formal Languages and Automata Theory · Computer Science 2019-09-16 Alexis Linard , Doina Bucur , Marielle Stoelinga

Event reconstruction is a fundamental part of the digital forensic process, helping to answer key questions like who, what, when, and how. A common way of accomplishing that is to use tools to create timelines, which are then analyzed.…

Cryptography and Security · Computer Science 2024-12-18 Céline Vanini , Chris Hargreaves , Frank Breitinger

In models to generate program source code from natural language, representing this code in a tree structure has been a common approach. However, existing methods often fail to generate complex code correctly due to a lack of ability to…

Computation and Language · Computer Science 2018-08-31 Shirley Anugrah Hayati , Raphael Olivier , Pravalika Avvaru , Pengcheng Yin , Anthony Tomasic , Graham Neubig

Test-time scaling has been widely adopted to enhance the capabilities of Large Language Model (LLM) agents in software engineering (SWE) tasks. However, the standard approach of repeatedly sampling trajectories from scratch is…

Software Engineering · Computer Science 2026-02-06 Yifeng Ding , Lingming Zhang

Nowadays, scientific databases have become the bread-and-butter of particle physicists. These databases must be maintained and checked repeatedly to insure the accuracy of their content. The COMPETE collaboration aims at motivating data…

The online reconstruction of muon tracks in High Energy Physics experiments is a highly demanding task, typically performed with programmable logic boards, such as FPGAs. Complex analytical algorithms are executed in a quasi-real-time…

High Energy Physics - Experiment · Physics 2022-12-21 Matteo Migliorini , Jacopo Pazzini , Andrea Triossi , Marco Zanetti , Alberto Zucchetta

Involving users in early phases of software development has become a common strategy as it enables developers to consider user needs from the beginning. Once a system is in production, new opportunities to observe, evaluate and learn from…

Information Retrieval · Computer Science 2022-10-25 Timo Breuer , Narges Tavakolpoursaleh , Johann Schaible , Daniel Hienert , Philipp Schaer , Leyla Jael Castro

Inclusive Monte-Carlo samples are indispensable for signal selection and background suppression in many high energy physics experiments. A clear knowledge of the physics processes involved in the samples, including the types of processes…

High Energy Physics - Experiment · Physics 2020-09-01 Xingyu Zhou , Shuxian Du , Gang Li , Chengping Shen

Machine learning (ML) plays an increasingly important role in both online and offline event reconstruction and identification at CMS experiment. A variety of ML techniques are used to improve the identification of physics objects. Dedicated…

High Energy Physics - Experiment · Physics 2026-02-10 Uttiya Sarkar

In some applications of reinforcement learning, a dataset of pre-collected experience is already available but it is also possible to acquire some additional online data to help improve the quality of the policy. However, it may be…

Machine Learning · Computer Science 2023-07-11 Ruiqi Zhang , Andrea Zanette

Evidence retrieval is a core part of automatic fact-checking. Prior work makes simplifying assumptions in retrieval that depart from real-world use cases: either no access to evidence, access to evidence curated by a human fact-checker, or…

Computation and Language · Computer Science 2024-06-18 Jifan Chen , Grace Kim , Aniruddh Sriram , Greg Durrett , Eunsol Choi

Autoregressive decoding makes the inference of Large Language Models (LLMs) time-consuming. In this paper, we reconsider speculative sampling and derive two key observations. Firstly, autoregression at the feature (second-to-top-layer)…

Machine Learning · Computer Science 2025-03-05 Yuhui Li , Fangyun Wei , Chao Zhang , Hongyang Zhang

The Monte Carlo for lepton pair production andtau decays consist of KKMC for lepton pair production, tauola for tau lepton decays and photos for radiative corrections in decays. An effort for adaptation of the system for precision data…

High Energy Physics - Phenomenology · Physics 2021-12-15 Sw. Banerjee , D. Biswas , T. Przedzinski , Z. Was