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ORCIDLawrence Chan
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2020 – today
- 2024
[j4]Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean:
Language Models Are Better Than Humans at Next-token Prediction. Trans. Mach. Learn. Res. 2024 (2024)- [c8]Richard Ngo, Lawrence Chan, Sören Mindermann:
The Alignment Problem from a Deep Learning Perspective. ICLR 2024 - [i11]Jason Gross, Rajashree Agrawal, Thomas Kwa, Euan Ong, Chun Hei Yip, Alex Gibson, Soufiane Noubir, Lawrence Chan:
Compact Proofs of Model Performance via Mechanistic Interpretability. CoRR abs/2406.11779 (2024) - [i10]Kaarel Hänni, Jake Mendel, Dmitry Vaintrob, Lawrence Chan:
Mathematical Models of Computation in Superposition. CoRR abs/2408.05451 (2024) - 2023
- [c7]Neel Nanda, Lawrence Chan, Tom Lieberum, Jess Smith, Jacob Steinhardt:
Progress measures for grokking via mechanistic interpretability. ICLR 2023 - [c6]Bilal Chughtai, Lawrence Chan, Neel Nanda:
A Toy Model of Universality: Reverse Engineering how Networks Learn Group Operations. ICML 2023: 6243-6267 - [i9]Neel Nanda, Lawrence Chan, Tom Lieberum, Jess Smith, Jacob Steinhardt:
Progress measures for grokking via mechanistic interpretability. CoRR abs/2301.05217 (2023) - [i8]Bilal Chughtai, Lawrence Chan, Neel Nanda:
A Toy Model of Universality: Reverse Engineering How Networks Learn Group Operations. CoRR abs/2302.03025 (2023) - [i7]Megan Kinniment, Lucas Jun Koba Sato, Haoxing Du, Brian Goodrich, Max Hasin, Lawrence Chan, Luke Harold Miles, Tao R. Lin, Hjalmar Wijk, Joel Burget, Aaron Ho, Elizabeth Barnes, Paul Christiano:
Evaluating Language-Model Agents on Realistic Autonomous Tasks. CoRR abs/2312.11671 (2023) - 2022
- [c5]Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas:
Adversarial training for high-stakes reliability. NeurIPS 2022 - [i6]Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas:
Adversarial Training for High-Stakes Reliability. CoRR abs/2205.01663 (2022) - [i5]Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean:
Language models are better than humans at next-token prediction. CoRR abs/2212.11281 (2022) - 2021
- [c4]Huiling Shao, Lawrence Chan, Fiona Chen, Qilin Ma, Zhiyu Shao, Heng Du:
A Fast-Processing Pipeline for Three-dimensional Visualization of Acute Ischemic Stroke lesion topography. BIBM 2021: 3207-3214 - [c3]Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan:
Optimal Cost Design for Model Predictive Control. L4DC 2021: 1205-1217 - [i4]Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan:
Optimal Cost Design for Model Predictive Control. CoRR abs/2104.11353 (2021) - [i3]Lawrence Chan, Andrew Critch, Anca D. Dragan:
Human irrationality: both bad and good for reward inference. CoRR abs/2111.06956 (2021) - 2020
- [i2]Harry Giles, Lawrence Chan:
Accounting for Human Learning when Inferring Human Preferences. CoRR abs/2011.05596 (2020)
2010 – 2019
- 2019
- [c2]Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan:
The Assistive Multi-Armed Bandit. HRI 2019: 354-363 - [i1]Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan:
The Assistive Multi-Armed Bandit. CoRR abs/1901.08654 (2019) - 2012
- [c1]Meyrick Chow, Lawrence Chan:
Clinical Decision Support using Traditional Chinese Medicine (TCM) Ontology and Text Similarity. Nursing Informatics 2012 - 2010
- [j3]Meyrick Chow
, Lawrence Chan:
Development and evaluation of a compartmental picture archiving and communications system model for integration and visualization of multidisciplinary biomedical data to facilitate student learning in an integrative health clinic. Comput. Educ. 54(3): 733-741 (2010)
2000 – 2009
- 2007
- [j2]Brent J. Liu, Zheng Zhou, Marco A. Gutierrez, Jorge Documet, Lawrence Chan, H. K. Huang:
International Internet2 connectivity and performance in medical imaging applications: Bridging the Americas to Asia. J. High Speed Networks 16(1): 5-20 (2007) - [j1]Zheng Zhou, Marco A. Gutierrez, Jorge Documet, Lawrence Chan, H. K. Huang, Brent J. Liu:
The role of a Data Grid in worldwide imaging-based clinical trials. J. High Speed Networks 16(1): 21-33 (2007)
Coauthor Index
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last updated on 2024-09-18 23:42 CEST by the dblp team
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