DeepPaperNote is an agent skill for deep-reading a single paper and generating high-quality Obsidian-style research notes. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
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Updated
May 27, 2026 - Python
DeepPaperNote is an agent skill for deep-reading a single paper and generating high-quality Obsidian-style research notes. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A markdown template for taking notes to summarize research papers.
Obsidian-first LLM Wiki skill pack with ontology-ready bootstrap, canonical JSONL truth layers, and optional graph projection.
Turning same-topic mixed materials into style-controlled Markdown notes, outlines, knowledge frameworks, and presentation outlines.
Research notes on maintaining and reasoning about LLM context windows across long-lived projects. Speculative ideas, heuristic boundaries, and design sketches without empirical validation.
Sunzi Reading / 孙子读论文 Skill: turn dense academic papers into short, warm, beginner-friendly explanations and reading notes.
Stanford AI for Lean Club progress on Erdős problems: papers, frontier notes, visualizer data, and Lean formalization.
An experimental research project developing a foundational theory of frameworks — the structures through which the human mind constructs and engages with reality.
A framework for clustering research notes
前沿物理仿真与智能感知技术调研资料库 | Frontier physics simulation research notes
Notes & experiments on LLMs, open-weight models, multimodal systems, and cloud deployment.
An introduction to actors with working Akka example to demonstrate an actor based approach to concurrency and it's affect of software design on scalability.
Vulnerability Research notes
SDFI emerges specifically under conditions of recursive self-description and sustained high semantic density, not in ordinary task-oriented interaction.This work is intended as a reference for researchers and system designers thinking about neutrality, termination behavior, and control surfaces in future AI systems.
Lab 137 — a place that both exists and does not exist. Talks, posters & research notes.
Notes & comparisons on storage options for large LLMs (Work-in-progress)
Research notes from hands-on experiments with model execution, training, and hybrid runtimes on the Apple Neural Engine. Findings only — no private-API names, no binaries.
Speculative concept note exploring the "editability surface" - the substrate primitives that allow intelligence to operate within a system and the dynamics that emerge once it does.
Add a description, image, and links to the research-notes topic page so that developers can more easily learn about it.
To associate your repository with the research-notes topic, visit your repo's landing page and select "manage topics."