• Wang, H. (2024). A Content-Based Novelty Measure for Scholarly Publications: A Proof of Concept. In: Sserwanga, I., et al. Wisdom, Well-Being, Win-Win. iConference 2024. Lecture Notes in Computer Science, vol 14598. Springer, Cham.

  • Tian, Z., Dong, X., Gao, F., Wang, H., & Lin, C. (2022). Mandarin Tone Sandhi Realization: Evidence from Large Speech Corpora. In Proc. Interspeech 2022, 5273-5277.

  • Wang, H. & Riddell A. (2022, Jun.). CCTAA: A Reproducible Corpus for Chinese Authorship Attribution Research. In Proceedings of the Language Resources and Evaluation Conference 2022 (pp. 5889-5893).

  • Wang, H., Xie X., & Riddell A. (2021, Nov.). The Challenge of Vernacular and Classical Chinese Cross-Register Authorship Attribution. In Proceedings of the Conference on Computational Humanities Research 2021 (pp. 299-309).

  • Riddell, A., Wang, H., & Juola, P. (2021, Sep.). A Call for Clarity in Contemporary Authorship Attribution Evaluation. In Proceedings of the International Conferences Recent Advances in Natural Language Processing (RANLP 2021): Deep Learning for Natural Language Processing Methods and Applications (pp. 1178-1183). https://10.26615/978-954-452-072-4_133.

  • Wang, H., Riddell, A., & Juola, P. (2021, Apr.). Mode Effects’ Challenge to Authorship Attribution. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021): Main Volume (pp. 1146-1155).