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Goal: build a durable corpus of high-impact autonomous driving papers, prioritizing papers with strong citation footprints, lasting conceptual importance, or clear influence on later systems. Use citation count as a fil…
Ilya Sutskever's curated reading list of ~30 papers and resources spanning the conceptual foundations of deep learning, from architecture breakthroughs to information theory and complexity. This list circulated widely a…
This batch creates the first real paper corpus for the wiki. It is intentionally mixed: classical autonomous driving, planning-oriented unified stacks, robotics VLA papers, and foundation-model papers that transfer into…
This page tracks the canonical LLM and adjacent foundation-model papers that matter for the autonomy side of the wiki. - wiki/sources/papers/on-the-opportunities-and-risks-of-foundation-models -- Stanford HAI report (20…
This is the master queue for source collection and ingest. 0. wiki/sources/initial-corpus-batch-01 1. wiki/sources/ilya-top-30 2. wiki/sources/autonomous-driving-seminal-papers 3. wiki/sources/vla-and-driving 4. wiki/so…
This queue spans general VLA foundations and driving-specific multimodal action papers. The AutoVLA corpus (18 papers, 2018–2025) provides the most comprehensive coverage of how language-vision models have been applied…