🧑‍🔬 Juan Zhai

🏛️ Affiliations

🎓University of Massachusetts AmherstAmherst Center · United States2023–2026 · 28 paperscurrent🎓Nanjing UniversityNanjing · China2014–2023 · 17 papers🎓Rutgers, The State University of New JerseyNew Brunswick · United States2017–2023 · 11 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition Inference (2026 · 1 citation)
   Automatically generated formal postconditions are hard to evaluate. Most prior checks only ask whether a postcondition holds on a correct implementation, so they miss whether it captures enough of the method's behavior. Completeness has mostly been judged by hand or with brittle string/AST matching on small…
2. Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code Datasets (2026)
   Public code corpora are often used to fine-tune code LLMs without their authors' consent. Dataset poisoning can discourage this by making such training unprofitable. The only earlier untargeted method for code, CoProtector, has two main weaknesses. Its edits either break compilation or only touch comments, and it…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Machine Translation Testing via Syntactic Tree Pruning ↗arXiv:2401.00751 · no summary yetQuanjun Zhang et al.2024 · 8 citations
2. POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition InferenceFindings of the Association for Computational LinguisticsGehao Zhang, Juan Zhai2026 · 1 citation
3. Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code DatasetsFindings of the Association for Computational LinguisticsYuan Xiao, Jiaming Wang, Yuchen Chen, et al.2026

🤝 Co-authors here

7 co-authors with a page, the most papers together first.

• Chunrong Fang
• Jiaming Wang
• Jin Song Dong
• Jun Sun
• Shiqing Ma
• Wei Song
• Zhenyu Chen

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2

Updated 2 November 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/juan-zhai/