A markdown template for taking notes to summarize research papers.

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.

Obsidian-first LLM Wiki skill pack with ontology-ready bootstrap, canonical JSONL truth layers, and optional graph projection.

A framework for clustering research notes

An experimental research project developing a foundational theory of frameworks — the structures through which the human mind constructs and engages with reality.

前沿物理仿真与智能感知技术调研资料库 | Frontier physics simulation research notes

Personal learning notebook on latent space engineering, representation geometry, and exploratory research notes.

Vulnerability Research notes

Notes & experiments on LLMs, open-weight models, multimodal systems, and cloud deployment.

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.

Website

Lab 137 — a place that both exists and does not exist. Talks, posters & research notes.

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.

Notes & comparisons on storage options for large LLMs (Work-in-progress)

Documentation, roadmap, technical notes, and future wiki resources for the Nominal Drift ecosystem.

Personal website of Iris Shen, focused on memory, evaluation, orchestration, and runtime systems for long-running AI agents.

Personal research notes, exploratory ideas, and early-stage project materials.

Research notes on causal machine learning, representation learning, and causal perspectives on language models.

A long-term, from-first-principles journey through machine learning and deep learning, centered on Dive into Deep Learning and extended with mathematical, probabilistic, and systems level understanding.