{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/formalalign-automated-alignment-evaluation","title":"FormalAlign: Automated Alignment Evaluation for Autoformalization","arxiv_id":"2410.10135","date":"2024-10-14","proceeding":null,"authors":["Jianqiao Lu","Yingjia Wan","Yinya Huang","Jing Xiong","Zhengying Liu","Zhijiang Guo"],"abstract":"Autoformalization aims to convert informal mathematical proofs into machine-verifiable formats, bridging the gap between natural and formal languages. However, ensuring semantic alignment between the informal and formalized statements remains challenging. Existing approaches heavily rely on manual verification, hindering scalability. To address this, we introduce \\textsc{FormalAlign}, the first automated framework designed for evaluating the alignment between natural and formal languages in autoformalization. \\textsc{FormalAlign} trains on both the autoformalization sequence generation task and the representational alignment between input and output, employing a dual loss that combines a pair of mutually enhancing autoformalization and alignment tasks. Evaluated across four benchmarks augmented by our proposed misalignment strategies, \\textsc{FormalAlign} demonstrates superior performance. In our experiments, \\textsc{FormalAlign} outperforms GPT-4, achieving an Alignment-Selection Score 11.58\\% higher on \\forml-Basic (99.21\\% vs. 88.91\\%) and 3.19\\% higher on MiniF2F-Valid (66.39\\% vs. 64.34\\%). This effective alignment evaluation significantly reduces the need for manual verification. Both the dataset and code can be accessed via~\\url{https://github.com/rookie-joe/FormalAlign}.","url_abs":"https://arxiv.org/abs/2410.10135v1","url_pdf":"https://arxiv.org/pdf/2410.10135v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"formalalign-automated-alignment-evaluation","repo_url":"https://github.com/rookie-joe/formalalign","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"mathematical-proofs","task_name":"Mathematical Proofs"},{"task_slug":null,"task_name":"valid"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"gpt-4","method_name":"GPT-4"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2410.10135","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.10135"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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