| MeLT: Message-level transformer with masked document representations as pre-training for stance detection M Matero, N Soni, N Balasubramanian, HA Schwartz Findings of the Association for Computational Linguistics: EMNLP 2021., 2021 | 23 | 2021 |
| Human language modeling N Soni, M Matero, N Balasubramanian, HA Schwartz Findings of the Association for Computational Linguistics: ACL 2022, 2022 | 15 | 2022 |
| I slept like a baby: Using human traits to characterize deceptive ChatGPT and human text S Giorgi, DM Markowitz, N Soni, V Varadarajan, S Mangalik, HA Schwartz International workshop on implicit author characterization from texts for …, 2023 | 8 | 2023 |
| WWBP-SQT-lite: Multi-level Models and Difference Embeddings for Moments of Change Identification in Mental Health Forums AV Ganesan, V Varadarajan, J Mittal, S Subrahmanya, M Matero, N Soni, ... Proceedings of the Eighth Workshop on Computational Linguistics and Clinical …, 2022 | 8* | 2022 |
| Detecting Dissonant Stance in Social Media: The Role of Topic Exposure V Varadarajan, N Soni, W Wang, C Luhmann, HA Schwartz, N Inoue Proceedings of the Fifth Workshop on Natural Language Processing and …, 2022 | 3 | 2022 |
| Robust language-based mental health assessments in time and space through social media S Mangalik, JC Eichstaedt, S Giorgi, J Mun, F Ahmed, G Gill, ... npj Digital Medicine 7 (1), 109, 2024 | 2 | 2024 |
| Large Human Language Models: A Need and the Challenges N Soni, HA Schwartz, J Sedoc, N Balasubramanian arXiv preprint arXiv:2312.07751, 2024 | 1 | 2024 |
| Comparing Pre-trained Human Language Models: Is it Better with Human Context as Groups, Individual Traits, or Both? N Soni, N Balasubramanian, HA Schwartz, D Hovy arXiv preprint arXiv:2401.12492, 2024 | 1* | 2024 |
| From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP AV Ganesan, S Mangalik, V Varadarajan, N Soni, S Juhng, J Sedoc, ... Proceedings of the 2024 Conference of the North American Chapter of the …, 2024 | | 2024 |
| Archetypes and Entropy: Theory-Driven Extraction of Evidence for Suicide Risk V Varadarajan, A Lahnala, AV Ganesan, G Dey, S Mangalik, AM Bucur, ... Proceedings of the 9th Workshop on Computational Linguistics and Clinical …, 2024 | | 2024 |
| Automatic Implicit Motives Codings are at Least as Accurate as Humans’ and 99% Faster AH Nilsson, JM Runge, AV Ganesan, CV NG, NS Lövenstierne, ONE Kjell | | |
H. Andrew SchwartzStony Brook University在 cs.stonybrook.edu 的电子邮件经过验证
