159 citations · 798 across the 116 of their papers we have counts for
122 papers
Theory-Level Autoformalization: From Isolated Statements to Unified Formal Knowledge Bases
Marcus J. Min, Mike He, Zhaoyu Li +5
Autoformalization translates informal natural language into formal, machine-verifiable languages. While most work focuses on individual statements, real formalization efforts are i…
Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning
Angel Tsai-Hsuan Chung, Botong Zhang, Ling-Chieh Kung +2
Generative AI (GenAI) is rapidly reshaping education by unlocking the potential for personalized tutoring. Yet, emerging platforms largely focus on GenAI chatbot tutors that reacti…
Improving Access to Essential Medicines via Decision-Aware Machine Learning
Angel Tsai-Hsuan Chung, Jatu Abdulai, Patrick Bayoh +4
A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources, particularly essential medicin…
A Hierarchy of Policy Learning Problems
Hamsa Bastani, Osbert Bastani, Shihan Chen
Policy learning has received substantial attention with the goal of learning policies from observational data for decision-making. A majority of work in this space has focused on d…
Theory-Scale Auto-Formalization of Logics for Computer Science
Yuming Feng, Frederick Pu, One An +5
Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-formalization, which coherent…
Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale
Haydn Jones, Yimeng Zeng, Alden Rose +11
Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are expensive to maintain, lag behind primary literature, and discard experimental cont…