arXiv subjects

Florian Wagner

Publications and source records attributed to Florian Wagner.

4 recordsLinked to original sources

arXiv2026

Lightweight Zero Trust via Automotive SDN

Zonal in-vehicle networks ship Ethernet, MACsec, and TSN, but treat the network itself as trusted: once configured at the factory, there is no standardized runtime way to easily revoke access, rotate keys, or contain a compromised ECU. Zero Trust Architecture targets exactly that gap, yet existing automotive ZTA proposals bolt on dedicated infrastructure that duplicates the SDN management plane already required to enable SDVs. Thus, ZTA is not yet adopted in the automotive domain, and the question remains: can we do better? We answer this in two steps. Step 1 analyses what Open Alliance TC17~v1.0 MACsec/MKA with pre-shared CAKs already provides in terms of NIST SP~800-207 ZTA tenets. Step 2 adds CORECONF/YANG management as proposed in Open Alliance TC19, maps the SDN Controller and Agents one-to-one onto NIST's PE, PA, and PEP. We then instantiate this with two YANG-based mechanisms: a network-access-control flow and a key-management scheme. The result fully covers five and two partially of the seven tenets with no ZTA-specific infrastructure added.

cs.CR↗

arXiv2026

ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents

We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents. OCR post-correction remains a long-standing challenge in digital heritage: large-scale collections of digitized documents are affected by legacy OCR errors, while re-digitization at scale remains impractical. Large language models (LLMs) offers a major opportunity to revisit this challenge, yet their effectiveness across languages, document types, and noise conditions - and their tendency to hallucinate - remains insufficiently understood. HIPE-OCRepair-2026 pursues two objectives: (i) to evaluate the capabilities of modern OCR post-correction systems, and (ii) to provide a reproducible evaluation framework anchored in the HIPE-OCRepair-2026 dataset, a harmonized multilingual resource consolidating existing and newly curated historical datasets. Participants were tasked with correcting noisy OCR transcripts from historical newspapers and printed works in English, French, and German (17th-20th century), working at the level of coherent transcription units (paragraphs or articles) without access to source images. The evaluation adopts a retrieval-oriented rather than diplomatic scoring approach, reflecting the practical use case of search and access over digitized collections. Four teams submitted systems ranging from zero-shot prompting to continued pre-training and fine-tuning, offering insights into the merits of different adaptation strategies. Results show that modern LLM-assisted systems can significantly improve OCR quality, but performance varies across datasets, languages, and noise levels. Over-correction on low-noise inputs emerges as a recurring challenge, highlighting the importance of evaluation beyond character error reduction. The dataset, scorer, and evaluation pipeline are publicly released to support future research.

cs.CL↗

arXiv2017

Enhancing laser-driven proton acceleration by using micro-pillar arrays at high drive energy

The interaction of micro- and nano-structured target surfaces with high-power laser pulses is being widely investigated for its unprecedented absorption efficiency. We have developed vertically aligned metallic micro-pillar arrays for laser-driven proton acceleration experiments. We demonstrate that such targets help strengthen interaction mechanisms when irradiated with high-energy-class laser pulses of intensities $\sim$ $10^{17-18}$ W/cm$^2$. In comparison with standard planar targets, we witness strongly enhanced hot-electron production and proton acceleration both in terms of maximum energies and particle numbers. Supporting our experimental results, two-dimensional particle-in-cell simulations show an increase in laser energy conversion into hot electrons, leading to stronger acceleration fields. This opens a window of opportunity for further improvements of laser-driven ion acceleration systems.

physics.plasm-ph↗

arXiv2015

The XL-mHG Test For Enrichment: A Technical Report

The minimum hypergeometric test (mHG) is a powerful nonparametric hypothesis test to detect enrichment in ranked binary lists. Here, I provide a detailed review of its definition, as well as the algorithms used in its implementation, which enable the efficient computation of an exact p-value. I then introduce a generalization of the mHG, termed XL-mHG, which provides additional control over the type of enrichment tested, and describe the precise algorithmic modifications necessary to compute its test statistic and p-value. The XL-mHG algorithm is a building block of GO-PCA, a recently proposed method for the exploratory analysis of gene expression data using prior knowledge.

stat.OT↗