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Technology for open-ended language generation, a key application of artificial intelligence, has advanced to a great extent in recent years.
Transformer-XL: Attentive language models beyond a fixed-length context
Dai, Z., Yang, Z., Yang, Y., Carbonell, J., Le, Q. V., & Salakhutdinov, R. (2019) · 1901
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Identifying and reducing gender bias in word-level language models
Bordia, S., & Bowman, S. R. (2019) · 1904
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The woman worked as a babysitter: On biases in language generation
Sheng, E., Chang, K.-W., Natarajan, P., & Peng, N. (2019) · 1909
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Benchmarking zero-shot text classification: Datasets, evaluation and entailment approach
Yin, W., Hay, J., & Roth, D. (2019) · 1909
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Huggingface’s transformers: State-of-the-art natural language processing
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M. et al. (2019) · 1910
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Ccnet: Extracting high quality monolingual datasets from web crawl data
Wenzek, G., Lachaux, M.-A., Conneau, A., Chaudhary, V., Guzmán, F., Joulin, A., & Grave, E. (2019) · 1911
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Personality structure: Emergence of the five-factor model
Digman, J. M. (1990) · 1990
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Linguistic styles: language use as an individual difference
Pennebaker, J. W., & King, L. A. (1999) · 1999
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The sixteen personality factor questionnaire (16PF)
Schuerger, J. M. (2000) · 2000
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The Eysenck personality scales: The Eysenck personality questionnaire-revised (EPQ-R) and the Eysenck personality profiler (EPP)
Miles, J., & Hempel, S. (2004) · 2004
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Stereoset: Measuring stereotypical bias in pretrained language models
Nadeem, M., Bethke, A., & Reddy, S. (2020) · 2004
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Language models are few-shot learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A. et al. (2020) · 2005
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A model for personality
Eysenck, H. J. (2012) · 2012
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Adam: A method for stochastic optimization
Kingma, D. P., & Ba, J. (2014) · 2014
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Zhu, Y., Kiros, R., Zemel, R., Salakhutdinov, R., Urtasun, R., Torralba, A., & Fidler, S. (2015) · 2015
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Bolukbasi, T., Chang, K.-W., Zou, J. Y., Saligrama, V., & Kalai, A. T. (2016) · 2016
Cited alongside, same era.
Github on bigquery: Analyze all the open source code
Hoffa, F. (2016) · 2016
Cited alongside, same era.
Analyzing personality through social media profile picture choice
Liu, L., Preotiuc-Pietro, D., Samani, Z. R., Moghaddam, M. E., & Ungar, L. (2016) · 2016
Cited alongside, same era.
Pointer sentinel mixture models
Merity, S., Xiong, C., Bradbury, J., & Socher, R. (2016) · 2016
Cited alongside, same era.
Stack exchange data dump
StackExchange (2017) · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017) · 2017
Xlnet: Generalized autoregressive pretraining for language understanding
Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R. R., & Le, Q. V. (2019) · 2019
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Introducing raffi: A personality adaptive conversational agent
Ahmad, R., Siemon, D., Fernau, D., & Robra-Bissantz, S. (2020) · 2020
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Zero-shot classify Big five personality traits
Derekmracek (2020) · 2020
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The pile: An 800gb dataset of diverse text for language modeling
Gao, L., Biderman, S., Black, S., Golding, L., Hoppe, T., Foster, C., Phang, J., He, H., Thite, A., Nabeshima, N. et al. (2020) · 2020
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Recent trends in deep learning based personality detection
Mehta, Y., Majumder, N., Gelbukh, A., & Cambria, E. (2020) · 2020
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · 2018
Cited alongside, same era.
Learning structured text representations
Liu, Y., & Lapata, M. (2018) · 2018
Cited alongside, same era.
Designing out stereotypes in artificial intelligence: Involving users in the personality design of a digital assistant
Spencer, J., Poggi, J., & Gheerawo, R. (2018) · 2018
Cited alongside, same era.
On application of natural language processing in machine translation
Zong, Z., & Hong, C. (2018) · 2018
Cited alongside, same era.
Automatic extraction of personality from text: Challenges and opportunities
Akrami, N., Fernquist, J., Isbister, T., Kaati, L., & Pelzer, B. (2019) · 2019
Cited alongside, same era.
Openwebtext corpus,
Gokaslan, A., & Cohen, V. (2019) · 2019
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2020) · 2020
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A literature review on question answering techniques, paradigms and systems
Soares, M. A. C., & Parreiras, F. S. (2020) · 2020
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Issues with entailment-based zero-shot text classification
Ma, T., Yao, J.-G., Lin, C.-Y., & Zhao, T. (2021) · 2021
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Evaluating state of the art in AI
SIOP (2019) · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Bai, Y., Jones, A., Ndousse, K., Askell, A., Chen, A., DasSarma, N., Drain, D., Fort, S., Ganguli, D., Henighan, T. et al. (2022) · 2022
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Solving quantitative reasoning problems with language models
Lewkowycz, A., Andreassen, A., Dohan, D., Dyer, E., Michalewski, H., Ramasesh, V., Slone, A., Anil, C., Schlag, I., Gutman-Solo, T. et al. (2022) · 2022
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Chatgpt: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope
Ray, P. P. (2023) · 2023
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Llama: Open and efficient foundation language models
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.-A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F. et al. (2023) · 2023
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A comprehensive capability analysis of gpt-3 and gpt-3.5 series models
Ye, J., Chen, X., Xu, N., Zu, C., Shao, Z., Liu, S., Cui, Y., Zhou, Z., Gong, C., Shen, Y. et al. (2023) · 2023
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