Althoff, T., Clark, K., & Leskovec, J. (2016). Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health. Transactions of the Association for Computational Linguistics, 4, 463–476. https://doi.org/10.1162/tacl_a_00111

Bao, E., Pérez, A., & Parapar, J. (2025). ReDSM5: A Reddit Dataset for DSM-5 Depression Detection (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2508.03399

Bn, S., Sherrill, A. M., Arriaga, R. I., Wiese, C. W., & Abdullah, S. (2025). Thousand Voices of Trauma: A Large-Scale Synthetic Dataset for Modeling Prolonged Exposure Therapy Conversations.

Cohan, A., Desmet, B., Yates, A., Soldaini, L., MacAvaney, S., & Goharian, N. (2018). SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions.

Gamoran, A., Kaplan, Y., Simchon, A., & Gilead, M. (2021). Using Psychologically-Informed Priors for Suicide Prediction in the CLPsych 2021 Shared Task.

Gollapalli, S. D., Ang, B. H., Du, M., & Ng, S.-K. (2024). Counseling Responses for Mental Health Forum Questions with Early Maladaptive Schema Prediction. In U. Endriss, F. S. Melo, K. Bach, A. Bugarín-Diz, J. M. Alonso-Moral, S. Barro, & F. Heintz (Eds.), Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/FAIA240785

Huang, J., Lam, M. H., Li, E. J., Ren, S., Wang, W., Jiao, W., Tu, Z., & Lyu, M. R. (2024). Apathetic or Empathetic? Evaluating LLMs’ Emotional Alignments with Humans.

Lee, J., Lim, K., Jung, Y.-C., & Kim, B.-H. (2025). PSYCHE: A Multi-faceted Patient Simulation Framework for Evaluation of Psychiatric Assessment Conversational Agents (No. arXiv:2501.01594). arXiv. https://doi.org/10.48550/arXiv.2501.01594

Li, T., Yang, S., Wu, J., Wei, J., Hu, L., Li, M., Wong, D. F., Oltmanns, J. R., & Wang, D. (2025). Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluation (No. arXiv:2502.17899). arXiv. https://doi.org/10.48550/arXiv.2502.17899

Liu, J. M., Li, D., Cao, H., Ren, T., Liao, Z., & Wu, J. (2023). ChatCounselor: A Large Language Models for Mental Health Support (No. arXiv:2309.15461). arXiv. https://doi.org/10.48550/arXiv.2309.15461

Liu, S., Zheng, C., Demasi, O., Sabour, S., Li, Y., Yu, Z., Jiang, Y., & Huang, M. (2021). Towards Emotional Support Dialog Systems. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) (pp. 3469–3483). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.acl-long.269

Malhotra, G., Waheed, A., Srivastava, A., Akhtar, M. S., & Chakraborty, T. (2022). Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations. Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 735–745. https://doi.org/10.1145/3488560.3498509

Owen, D., Collados, J. C., & Espinosa-Anke, L. (2020). Towards Preemptive Detection of Depression and Anxiety in Twitter (No. arXiv:2011.05249). arXiv. https://doi.org/10.48550/arXiv.2011.05249

Qiu, H., & Lan, Z. (2024). Interactive Agents: Simulating Counselor-Client Psychological Counseling via Role-Playing LLM-to-LLM Interactions (No. arXiv:2408.15787). arXiv. https://doi.org/10.48550/arXiv.2408.15787

Raihan, N., Puspo, S. S. C., Farabi, S., Bucur, A.-M., Ranasinghe, T., & Zampieri, M. (2024). MentalHelp: A Multi-Task Dataset for Mental Health in Social Media. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 11196–11203). ELRA and ICCL. https://aclanthology.org/2024.lrec-main.977

Sharma, A., Miner, A., Atkins, D., & Althoff, T. (2020). A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support. In B. Webber, T. Cohn, Y. He, & Y. Liu (Eds.), Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 5263–5276). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.425

Shreevastava, S., & Foltz, P. (2021). Detecting Cognitive Distortions from Patient-Therapist Interactions. Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access, 151–158. https://doi.org/10.18653/v1/2021.clpsych-1.17

Singh, L. G., Middleton, S. E., Azim, T., Nichele, E., Lyu, P., & Garcia, S. D. O. (n.d.). ConversationMoC: Encoding Conversational Dynamics using Multiplex Network for Identifying Moment of Change in Mood and Mental Health Classification.

Sun, H., Lin, Z., Zheng, C., Liu, S., & Huang, M. (2021). PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 1489–1503. https://doi.org/10.18653/v1/2021.findings-acl.130

Turcan, E., & McKeown, K. (2019). Dreaddit: A Reddit Dataset for Stress Analysis in Social Media. Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019), 97–107. https://doi.org/10.18653/v1/D19-6213

Welivita, A., & Pu, P. (2022). Curating a Large-Scale Motivational Interviewing Dataset Using Peer Support Forums. In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, & S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics (pp. 3315–3330). International Committee on Computational Linguistics. https://aclanthology.org/2022.coling-1.293/

Welivita, A., Yeh, C.-H., & Pu, P. (2023). Empathetic Response Generation for Distress Support. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 632–644. https://doi.org/10.18653/v1/2023.sigdial-1.59

Wu, Z., Balloccu, S., Kumar, V., Helaoui, R., Reiter, E., Reforgiato Recupero, D., & Riboni, D. (2022). Anno-MI: A Dataset of Expert-Annotated Counselling Dialogues. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6177–6181. https://doi.org/10.1109/ICASSP43922.2022.9746035

Xu, J., Wei, T., Hou, B., Orzechowski, P., Yang, S., Jin, R., Paulbeck, R., Wagenaar, J., Demiris, G., & Shen, L. (2025). MentalChat16K: A Benchmark Dataset for Conversational Mental Health Assistance (No. arXiv:2503.13509). arXiv. https://doi.org/10.48550/arXiv.2503.13509

Yeh, C.-H., & Welivita, K. A. (n.d.). A Dialogue Dataset Containing Emotional Support for People in Distress.

Zhang, M., Yang, X., Zhang, X., Labrum, T., Chiu, J. C., Eack, S. M., Fang, F., Wang, W. Y., & Chen, Z. Z. (2025). CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy (No. arXiv:2410.13218). arXiv. https://doi.org/10.48550/arXiv.2410.13218

Zheng, C., Sabour, S., Wen, J., Zhang, Z., & Huang, M. (2023). AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation. Findings of the Association for Computational Linguistics: ACL 2023, 1552–1568. https://doi.org/10.18653/v1/2023.findings-acl.99