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Language technologies have made enormous progress, especially with the introduction of large language models (LLMs).
Language models are few-shot learners
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Joshi, Pratik, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury. 2020 · 2020
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Emoticon: Context-aware multimodal emotion recognition using frege’s principle
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Predictive biases in natural language processing models: A conceptual framework and overview
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More than meets the tie: Examining the role of interpersonal relationships in social networks
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Latent hatred: A benchmark for understanding implicit hate speech
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The importance of modeling social factors of language: Theory and practice
Hovy, Dirk and Diyi Yang. 2021 · 2021
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Globalbench: A benchmark for global progress in natural language processing
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What’s the meaning of superhuman performance in today’s NLU?
Tedeschi, Simone, Johan Bos, Thierry Declerck, Jan Hajič, Daniel Hershcovich, Eduard Hovy, Alexander Koller, Simon Krek, Steven Schockaert, Rico Sennrich, Ekaterina Shutova, and Roberto Navigli. 2023 · 2023
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Exploring collaboration mechanisms for llm agents: A social psychology view
Zhang, Jintian, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, and Shumin Deng. 2023 · 2023
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Can large language models transform computational social science?
Ziems, Caleb, Omar Shaikh, Zhehao Zhang, William Held, Jiaao Chen, and Diyi Yang. 2023 · 2023
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Centering the speech community
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Real or robotic? assessing whether llms accurately simulate qualities of human responses in dialogue
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Stereotype or personalization? user identity biases chatbot recommendations
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The potential and challenges of evaluating attitudes, opinions, and values in large language models
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Gpt is an effective tool for multilingual psychological text analysis
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Unintended impacts of LLM alignment on global representation
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