Index
This is the navigation entry point for the wiki.
Overview
- Overview - High-level map of the research space across ML, autonomous driving, robotics, and foundation-model-driven autonomy.
Concepts
- Machine Learning - Canonical page for the broader ML framing and the subfields relevant to this vault.
- Autonomous Driving - System-level framing of autonomy stacks, constraints, and research decomposition.
- Robotics - Robotics context, transfer opportunities, and where robotics assumptions diverge from driving.
- Vision Language Action - VLA framing from general robotics to driving-specific action-conditioned models.
- End To End Architectures - Definitions and tensions between modular, hybrid, and end-to-end systems.
- Perception - Scene understanding, representation learning, sensor fusion, and map reasoning.
- Prediction - Behavior forecasting, interaction modeling, uncertainty, and evaluation.
- Planning - Decision making, trajectory generation, control abstractions, and closed-loop concerns.
- Foundation Models - LLM, VLM, and multimodal foundation-model ideas that affect autonomy.
Taxonomies
- Research Map - A practical taxonomy for organizing the field and routing new sources to the right pages.
Comparisons
- Modular Vs End To End - Comparison page tracking definitions, tradeoffs, and recurring confusions.
Syntheses
- Research Thesis - Evolving thesis about where the field is going and which bets matter most.
- Frontend Strategy - Tradeoffs between the included Flask viewer and Obsidian-oriented publishing frontends.
Queries
- Open Questions - Priority research questions and unresolved tensions the wiki should keep testing.
- Paper Fact Check Tracker - Corpus-wide paper validation tracker covering metadata checks and sentence-level faithfulness audit status.
Source Programs
- Source Ingest Queue - Master queue for source acquisition and ingest.
- Initial Corpus Batch 01 - First real corpus batch with 27 seeded paper pages across driving, VLA, and foundation models.
- Ilya Top 30 - Complete canonical list of Ilya Sutskever's 30 recommended papers, all ingested with full summaries.
- Autonomous Driving Seminal Papers - High-impact autonomous driving papers across perception, prediction, planning, and e2e systems (21 ingested).
- Vla And Driving - VLM/VLA sources spanning robotics and autonomous driving, including full AutoVLA corpus of 18 papers (2018–2025).
- Llm Seminal Papers - Seed list for canonical LLM and foundation-model papers.