Deyuan Mike He — accepted AI-conference papers

2026

AlgoVeri: An Aligned Benchmark for Verified Code Generation on Classical Algorithms

Haoyu Zhao, Ziran Yang, Jiawei Li, Deyuan Mike He, Zenan Li, Chi Jin +3

ICML 2026spotlight

Vericoding refers to the generation of formally verified code from rigorous specifications. Recent AI models show promise in vericoding, but a unified methodology for cross-paradigm evaluation is lacking. Existing benchmarks test only an individual language/tool (e.g., Dafny, Verus, and Lean) and ea…

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2026

Position: The Case for Theory-Level Autoformalization

Marcus Min, Deyuan Mike He, Zhaoyu Li, Zixuan Yi, Sharad Malik, Aarti Gupta +2

ICML 2026spotlight

Autoformalization, translating informal natural language into formal, machine-verifiable languages, has been framed as a tool to generate training data for neural theorem provers, with most work focusing on individual statements. This position paper argues for theory-level autoformalization: formali…

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