Additional Campus Affiliations
Professor, Siebel School of Computing and Data Science
Professor, Coordinated Science Lab
Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
Recent Publications
Haldar, R., & Hockenmaier, J. (2024). Analyzing the Performance of Large Language Models on Code Summarization. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings (pp. 995-1008). (2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings). European Language Resources Association (ELRA).
Jung, Y., Hockenmaier, J., & Golparvar-Fard, M. (2024). Feasibility analysis on the use of NLP-based schedule analytics for 4D project planning and controls. In Y. Turkan, J. Louis, F. Leite, & S. Ergan (Eds.), Computing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023 (pp. 42-50). (Computing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023). American Society of Civil Engineers. https://doi.org/10.1061/9780784485224.006
Jung, Y., Hockenmaier, J., & Golparvar-Fard, M. (2024). Transformer language model for mapping construction schedule activities to uniformat categories. Automation in Construction, 157, Article 105183. https://doi.org/10.1016/j.autcon.2023.105183
Canby, M. E., & Hockenmaier, J. (2023). A Framework for Bidirectional Decoding: Case Study in Morphological Inflection. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 4485-4507). (Findings of the Association for Computational Linguistics: EMNLP 2023). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-emnlp.297
Cho, I., Jung, Y., & Hockenmaier, J. (2023). SIR-ABSC: Incorporating Syntax into RoBERTa-based Sentiment Analysis Models with a Special Aggregator Token. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 8535-8550). (Findings of the Association for Computational Linguistics: EMNLP 2023). Association for Computational Linguistics (ACL).