5 papers
Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
Xiaoyang Liu, Zineng Dong, Yifan Bai +3
Statement autoformalization acts as a critical bridge between human mathematics and formal mathematics by translating natural language problems into formal language. While prior wo…
VeriScale: Adversarial Test-Suite Scaling for Verifiable Code Generation
Yifan Bai, Xiaoyang Liu, Zihao Mou +7
As large language models (LLMs) are increasingly deployed for software engineering, constructing high-quality benchmarks is crucial for evaluating not just the functional correctne…
ASSESS: A Semantic and Structural Evaluation Framework for Statement Similarity
Xiaoyang Liu, Tao Zhu, Zineng Dong +5
Despite significant strides in statement autoformalization, a critical gap remains in the development of automated evaluation metrics capable of assessing formal translation qualit…
ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data
Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang +5
Autoformalization, the automatic translation of mathematical content from natural language into machine-verifiable formal languages, has seen significant progress driven by advance…
Generalized Tree Edit Distance (GTED): A Faithful Evaluation Metric for Statement Autoformalization
Yuntian Liu, Tao Zhu, Xiaoyang Liu +6
Statement autoformalization, the automated translation of statements from natural language into formal languages, has become a subject of extensive research, yet the development of…