Allison (Tsz Kwan) Lau
I am a 4th-year undergrad student in computer science and physics at the University of Toronto , where I am currently working under the supervision of Prof. Rahul Krishnan.
✉️ allison.lau@mail.utoronto.ca
Research Interest: I am interested in developing and improving fine-tuning and alignment methods for Large Language Models (LLMs), and Reinforcement Learning from Human Feedback (RLHF). I am also interested in intrepretability of LLMs, and would love to explore computational social science as well. Prior to my work in LLMs, I worked on several projects in optical/computational imaging and graphics.
.. Last updated: Nov 21, 2024
News
- Dec 10:: I am in Vancouver for NeurIPS! I'll be presenting a poster on Dec 14 (Sat) at 4:30-5:30pm: Personalized Adaptation via In-Context Preference Learning @ AFM
Publications
[0] Personalized Adaptation via In-Context Preference Learning
Allison Lau, Younwoo Choi, Vahid Balazadeh, Keertana Chidambaram, Vasilis Syrgkanis, Rahul Krishnan
NeurIPS 2024 Workshop on Adaptive Foundation Models
We introduce the Preference Pretrained Transformer (PPT), a method for adaptive personalization using online user feedback. PPT combines offline training with a history-dependent loss and online adaptation through in-context learning to dynamically align with individual preferences.
[1] Analyzing the effect of undermining on suture forces during simulated skin flap surgeries with a three-dimensional finite element method
Wenzhangzhi Guo, Allison Lau, Joel C. Davies, Vito Forte, Eitan Grinspun, Lueder Alexander Kahrs
EG VCBM 2024
We developed a 3D mesh generation pipeline to model skin flap surgeries and systematically explored variations in undermining regions. We conducted suture force and suture line analyses to assess outcomes across these regions, and vsualized skin flap procedures using personalized 3D face scans for enhanced patient-specific planning.
[2] Beyond CCDs: Characterization of sCMOS detectors for optical astronomy
Aditya Khandelwal, Sarik Jeram, Ryan Dungee, Albert W.K. Lau, Allison Lau, Ethen Sun, Phil Van-Lane, Shaojie Chen, Aaron Tohuvavohu, Ting S. Li
SPIE Astronomical Telescopes + Instrumentation 2024
We highlight the suitability of sCMOS detectors for space imaging, evaluating detectors like the Teledyne Prime 95B for wide fields and Hamamatsu Orca-Quest for deep-sky imaging, which demonstrated exceptional performance and low noise levels.