From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 59 more institutions on single bylines are not listed.

Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6Artificial Intelligence · 2 works Computer Science · 2 works Computational Theory and Mathematics · 1 work Mathematics · 1 work Safety Research · 1 work Social Sciences · 1 work

🧭 Topics 1Interpretability · 1 work

Works by year

2020s

20231 paper 20221 paper

Papers

The most cited first (OpenAlex and our library).

Progress measures for grokking via mechanistic interpretability (2023 · 228 citations)
Deep networks sometimes gain new abilities abruptly, which makes their behavior hard to anticipate. This work asks whether such jumps hide smooth underlying progress, and whether interpretability can reveal it. The test case is grokking: small transformers learning addition modulo a prime first memorize the training…
The Alignment Problem from a Deep Learning Perspective (2022 · 121 citations)
The paper asks whether long-standing worries about misaligned AGI still hold when they are tied to current deep learning practice rather than to abstract arguments from classical AI.

Co-authors here

4 co-authors with a page, the most papers together first.

Cited by

Papers of our library cite their works 237 times (of the 149,439 papers whose bibliographies we read); 54 citing papers with a page here →.

Updated 2 November 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/lawrence-chan/

🧑‍🔬 Lawrence Chan

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

🔗 Cited by

Lawrence Chan

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here

Cited by