Hantao Lou
Peking University (student)
Peking University (student)
Hantao worked on developmental interpretability and model auditing under the mentorship of Evan Hubinger during the 2024 MATS summer cohort remotely. He analyzed the shift of interpretable features before/after finetuning, thereby developing a method to improve model auditing. Before MATS, Hantao is an undergraduate student at Peking University and a visiting student at PAIR Lab. He is now continuing his research in MATS extension to gain a deeper insight into interpretability and alignment.
The Summer 2024 cohort marked a significant expansion, supporting approximately 90 scholars with 40 mentors—the broadest mentor selection in MATS history. This cohort incorporated MATS as a 501(c)(3) nonprofit organization, formalizing its institutional structure. The program expanded its research portfolio to include at least four governance mentors alongside technical research streams, reflecting growing interest in AI policy and technical governance work. The 10-week research phase continued in Berkeley, with scholars conducting work across mechanistic interpretability, evaluations, scalable oversight, and governance research.Notable outputs from this cohort include research on targeted manipulation and deception in LLMs trained on user feedback, which was accepted to NeurIPS workshops, and contributions to an AI safety via debate paper that won best paper at ICML 2024. One scholar co-founded Decode Research, a new AI safety organization focused on building interpretability tools.
Hantao Lou
