1 citations · 1 across the 5 of their papers we have counts for
7 papers
Vero: Can AI Agents Build Formally Verified Software Repositories?
Zhe Ye, Hantao Lou, Yuechun Sun +8
AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code. Verified code generation, in which an agent produces both an…
P: Joint Program-and-Proof Planning for Verified Code Generation
Zenan Li, Ziran Yang, Peiyang Song +2
Verified code generation asks a large language model (LLM) to generate both an executable program and a machine-checkable proof that the program meets a formal specification, promi…
The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Pengrui Han, Rafal Kocielnik, Peiyang Song +4
Personality traits have long been studied as predictors of human behavior. Recent advances in Large Language Models (LLMs) suggest similar patterns may emerge in artificial systems…
LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
Robert Joseph George, Suozhi Huang, Peiyang Song +1
Mathematical reasoning remains a significant challenge for Large Language Models (LLMs) due to hallucinations. When combined with formal proof assistants like Lean, these hallucina…
LeanAgent: Lifelong Learning for Formal Theorem Proving
Adarsh Kumarappan, Mo Tiwari, Peiyang Song +3
Large Language Models (LLMs) have been successful in mathematical reasoning tasks such as formal theorem proving when integrated with interactive proof assistants like Lean. Existi…
Creative and Context-Aware Translation of East Asian Idioms with GPT-4
Kenan Tang, Peiyang Song, Yao Qin +1
As a type of figurative language, an East Asian idiom condenses rich cultural background into only a few characters. Translating such idioms is challenging for human translators, w…