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Show HN: Lint Your Markdown with ESLint
Important If you like this package, please give it a star on GitHub!⭐ Your support helps us improve and maintain the project. Lint your Markdown with ESLint.
SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents
Announce Type: replace Abstract: LLM agents increasingly rely on reusable skills (e.g., SKILL markdown files) to execute complex tasks, yet these artifacts lack portability: agent frameworks are highly sensitive to prompt formatting, leading to a large performance variation for the same skill. Nevertheless, most skills are authored once as format-agnostic Markdown, necessitating costly per-framework rewrites and also leaving security largely unaddressed, with widespread vulnerabilities in...
Pandoc Templates
Results A clean pandoc LaTeX template to convert your markdown files to PDF or LaTeX. It is designed for lecture notes and exercises with a focus on computer science. The template is compatible with pandoc 3.
MalSkillBench: A Runtime-Verified Benchmark of Malicious Agent Skills
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SkCC: Portable and Secure Skill Compilation for Cross-Framework LLM Agents
arXiv:2605.03353v3 Announce Type: replace Abstract: LLM agents increasingly rely on reusable skills (e.g., $SKILL.md$ ) to execute complex tasks, yet these artifacts lack portability: agent frameworks are highly sensitive to prompt formatting, leading to a large performance variation for the same skill. Nevertheless, most skills are authored once as format-agnostic Markdown, necessitating costly per-framework rewrites and also leaving security largely unaddressed, with widespread...
Any2Poster: Any-Source Poster Generation Across Modalities and Domains
Announce Type: new Abstract: Visual posters are a compact medium for communicating dense information, yet progress on automatic poster generation remains difficult to measure because existing evaluations are often restricted to paper-only inputs, narrow domains, or surface-level visual similarity. We introduce Any2Poster Bench, a benchmark for any-source poster generation that evaluates systems across eight input modalities--PDFs, URLs, PPTX, DOCX, Markdown, LaTeX, notebooks, and videos--and...
Semantic Triplet Restoration: A Novel Protocol for Hierarchical Table Understanding in Large Language Models
arXiv:2605.31550v1 Announce Type: new Abstract: Table question answering requires models to recover semantic relations encoded implicitly by two-dimensional layout, merged cells, and hierarchical headers. Current pipelines typically use HTML or Markdown as intermediate table representations, but these layout-oriented serializations introduce markup overhead and require large language models to infer header-cell alignments from row and column spans. We propose Semantic Triplet Restoration...
RealDocBench: A Benchmark for Field-Level QA and Layout Understanding on Real-World Regulated Documents
arXiv:2606.07401v1 Announce Type: new Abstract: Document parsing systems are increasingly deployed in high-stakes, regulated workflows such as mortgage underwriting, financial reporting, supply-chain logistics, and clinical records. Yet most public benchmarks evaluate parsers on clean academic layouts or synthetic prose, and report a single OCR or markdown-level similarity score. Such documents and metrics correlate poorly with what downstream agents actually need: the correct value for a...
TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs
arXiv:2606.09578v1 Announce Type: new Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) are increasingly evaluated on table reasoning tasks, but the role of table representation remains under-explored. In practice, the same table content may appear in different structural formats, such as HTML, Markdown, and LaTeX, or as rendered images. However, existing evaluations often let content, format, layout, and modality vary together, making it difficult to isolate...