|
[1]
|
Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural Machine Translation by Jointly Learning to Align and Translate. arXiv: 1409.0473.
|
|
[2]
|
Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). Threat-Related Attentional Bias in Anxious and Nonanxious Individuals: A Meta-Analytic Study. Psychological Bulletin, 133, 1-24.[CrossRef] [PubMed]
|
|
[3]
|
Bolukbasi, T., Chang, K. W., Zou, J. Y., Saligrama, V., & Kalai, A. T. (2016). Man Is to Computer Programmer as Woman Is to Homemaker? Debiasing Word Embeddings. Advances in Neural Information Processing Systems, 29, 4349-4357.
|
|
[4]
|
Brewin, C. R. (2006). Understanding Cognitive Behaviour Therapy: A Retrieval Competition Account. Behaviour Research and Therapy, 44, 765-784.[CrossRef] [PubMed]
|
|
[5]
|
Brewin, C. R. (2011). The Nature and Significance of Memory Disturbance in Posttraumatic Stress Disorder. Annual Review of Clinical Psychology, 7, 203-227.[CrossRef] [PubMed]
|
|
[6]
|
Broadbent, D. E. (1958). Perception and Communication. Pergamon Press.
|
|
[7]
|
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Amodei, D. et al. (2020). Language Models Are Few-Shot Learners. Advances in Neural Information Processing Systems, 33, 1877-1901.
|
|
[8]
|
Browning, M., Holmes, E. A., & Harmer, C. J. (2010). The Modification of Attentional Bias to Emotional Information: A Review of the Techniques, Mechanisms, and Relevance to Emotional Disorders. Cognitive, Affective, & Behavioral Neuroscience, 10, 8-20.[CrossRef] [PubMed]
|
|
[9]
|
Browning, M., Holmes, E. A., Charles, M., Cowen, P. J., & Harmer, C. J. (2012). Using Attentional Bias Modification as a Cognitive Vaccine against Depression. Biological Psychiatry, 72, 572-579.[CrossRef] [PubMed]
|
|
[10]
|
Bylsma, L. M., Morris, B. H., & Rottenberg, J. (2021). A Meta-Analysis of Emotional Reactivity in Major Depressive Disorder. Clinical Psychology Review, 31, 1397-1407.
|
|
[11]
|
Cisler, J. M., & Koster, E. H. W. (2010). Mechanisms of Attentional Biases Towards Threat in Anxiety Disorders: An Integrative Review. Clinical Psychology Review, 30, 203-216.[CrossRef] [PubMed]
|
|
[12]
|
Clark, K., Khandelwal, U., Levy, O., & Manning, C. D. (2019). What Does BERT Look At? An Analysis of Bert’s Attention. In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP (pp. 276-286). Association for Computational Linguistics.[CrossRef]
|
|
[13]
|
Cristea, I. A., Kok, R. N., & Cuijpers, P. (2015). Efficacy of Cognitive Bias Modification Interventions in Anxiety and Depression: Meta-Analysis. British Journal of Psychiatry, 206, 7-16.[CrossRef] [PubMed]
|
|
[14]
|
Ehlers, A., & Clark, D. M. (2000). A Cognitive Model of Posttraumatic Stress Disorder. Behaviour Research and Therapy, 38, 319-345.[CrossRef] [PubMed]
|
|
[15]
|
Gotlib, I. H., & Joormann, J. (2010). Cognition and Depression: Current Status and Future Directions. Annual Review of Clinical Psychology, 6, 285-312.[CrossRef] [PubMed]
|
|
[16]
|
Hakamata, Y., Lissek, S., Bar-Haim, Y., Britton, J. C., Fox, N. A., Leibenluft, E. et al. (2010). Attention Bias Modification Treatment: A Meta-Analysis toward the Establishment of Novel Treatment for Anxiety. Biological Psychiatry, 68, 982-990.[CrossRef] [PubMed]
|
|
[17]
|
Heeren, A., Mogoaşe, C., Philippot, P., & McNally, R. J. (2015). Attention Bias Modification for Social Anxiety: A Systematic Review and Meta-Analysis. International Journal of Cognitive Therapy, 8, 29-46.
|
|
[18]
|
Howard, J., & Ruder, S. (2018). Universal Language Model Fine-Tuning for Text Classification. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 328-339). Association for Computational Linguistics.[CrossRef]
|
|
[19]
|
Jung, C. G. (1934). The Archetypes and the Collective Unconscious. Princeton University Press.
|
|
[20]
|
Keng, S., Smoski, M. J., & Robins, C. J. (2011). Effects of Mindfulness on Psychological Health: A Review of Empirical Studies. Clinical Psychology Review, 31, 1041-1056.[CrossRef] [PubMed]
|
|
[21]
|
Kircanski, K., Joormann, J., & Gotlib, I. H. (2012). Cognitive Aspects of Depression. WIREs Cognitive Science, 3, 301-313.[CrossRef] [PubMed]
|
|
[22]
|
Kuckertz, J. M., Gildebrant, E., Liliequist, B., Karlström, P., Väppling, C., Bodlund, O. et al. (2014). Moderation and Mediation of the Effect of Attention Training in Social Anxiety Disorder. Behaviour Research and Therapy, 53, 30-40.[CrossRef] [PubMed]
|
|
[23]
|
MacLeod, C., Rutherford, E., Campbell, L., Ebsworthy, G., & Holker, L. (2002). Selective Attention and Emotional Vulnerability: Assessing the Causal Basis of Their Association through the Experimental Manipulation of Attentional Bias. Journal of Abnormal Psychology, 111, 107-123.[CrossRef] [PubMed]
|
|
[24]
|
Maples-Keller, J. L., Bunnell, B. E., Kim, S., & Rothbaum, B. O. (2017). The Use of Virtual Reality Technology in the Treatment of Anxiety and Other Psychiatric Disorders. Harvard Review of Psychiatry, 25, 103-113.[CrossRef] [PubMed]
|
|
[25]
|
Mathews, A., & MacLeod, C. (2005). Cognitive Vulnerability to Emotional Disorders. Annual Review of Clinical Psychology, 1, 167-195.[CrossRef] [PubMed]
|
|
[26]
|
Michael, T., Ehlers, A., Halligan, S. L., & Clark, D. M. (2005). Unwanted Memories of Assault: What Intrusion Characteristics Are Associated with PTSD? Behaviour Research and Therapy, 43, 613-628.[CrossRef] [PubMed]
|
|
[27]
|
Roesler, C. (2019). Evidence for the Effectiveness of Jungian Psychotherapy: A Review of Empirical Studies. Behavioral Sciences, 3, 562-575.
|
|
[28]
|
Stein, M. (2019). Jung’s Map of the Soul: An Introduction. Open Court Publishing.
|
|
[29]
|
Treisman, A. M., & Gelade, G. (1980). A Feature-Integration Theory of Attention. Cognitive Psychology, 12, 97-136.[CrossRef] [PubMed]
|
|
[30]
|
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Polosukhin, I. et al. (2017). Attention Is All You Need. Advances in Neural Information Processing Systems, 30, 5998-6008.
|
|
[31]
|
Voita, E., Talbot, D., Moiseev, F., Sennrich, R., & Titov, I. (2019). Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 5797-5808). Association for Computational Linguistics.[CrossRef]
|