Challenge: This tutorial bridges psychology and NLP to clarify cognitive effects and biases in large language models.
Approach: This tutorial bridges psychology and NLP to clarify cognitive effects and biases in large language models.
Outcome: This tutorial bridges psychology and NLP to clarify cognitive effects and biases in large language models.

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Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorials (2021.naacl-tutorials)

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Challenge: NAACL 2021 tutorials session is a conference for researchers to present on a topic of importance . a total of 35 tutorial submissions were received, of which 6 were selected for presentation .
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A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations (2024.emnlp-main)

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Challenge: Large Language Models (LLMs) have gained significant attention due to their capabilities in performing diverse tasks across domains.
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Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials (N19-5)

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Challenge: NAACL-HLT 2019 tutorials session is organized to give conference attendees a comprehensive introduction to a topic of importance drawn from our rapidly growing and changing research field from expert researchers.
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On Measures of Biases and Harms in NLP (2022.findings-aacl)

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Challenge: Recent studies show that natural language processing (NLP) technologies propagate societal biases about demographic groups associated with attributes such as gender, race, and nationality.
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How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances (2023.emnlp-main)

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Challenge: Large language models (LLMs) are impressive in solving tasks, but they can quickly be outdated after deployment.
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Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts) (2024.naacl-tutorials)

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Challenge: NAACL 2024 tutorial sessions are a cornerstone event of the conference . a total of 27 tutorial submissions were received, and 6 were selected for presentation .
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Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview (2020.acl-main)

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Challenge: a growing number of studies address the effect of bias on predictions, but no unifying framework exists . a general phenomenon of biased predictive models in NLP is not recent, authors say .
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Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts) (2025.naacl-tutorial)

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Challenge: NAACL 2025 tutorial sessions are a cornerstone event of the conference . tutorials are designed to equip you with the latest insights, tools, and methodologies .
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Addressing Bias and Hallucination in Large Language Models (2024.lrec-tutorials)

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Challenge: This tutorial provides a comprehensive overview of two critical aspects of Large Language Models: bias and hallucination.
Approach: This tutorial provides an overview of two critical aspects of Large Language Models: bias and hallucination.
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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts) (2025.acl-tutorials)

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Challenge: ACL 2025 tutorial sessions are a cornerstone event of the conference . 76 tutorial submissions were received this year, many of which were very engaging .
Approach: 76 tutorial submissions were received this year for the tutorial session at ACL 2025 . the tutorials are designed to equip you with the latest insights, tools, and methodologies .
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