Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 5: Tutorial Abstracts)
Catch Me If You GPT: Tutorial on Deepfake Texts (2024.naacl-tutorials)
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| Challenge: | In recent years, natural language generation (NLG) techniques have advanced, but pose new security risks . this tutorial will be 3 hours long with a mix of lecture and hands-on examples for interactive audience participation. |
| Approach: | They present a tutorial on the security of natural language generation (NLG) they review the latest literature on the detection and obfuscation of deepfake text authorships . |
| Outcome: | This tutorial reviews the latest literature on the detection and obfuscation of deepfake text authorships. |
Combating Security and Privacy Issues in the Era of Large Language Models (2024.naacl-tutorials)
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| Challenge: | a tutorial aims to provide a summary of risks and vulnerabilities in large language models . a number of studies have focused on security, privacy and copyright aspects of LLMs . |
| Approach: | This tutorial seeks to provide a systematic summary of risks and vulnerabilities in large language models . authors will discuss security, privacy and copyright aspects of LLMs . |
| Outcome: | This tutorial aims to provide a systematic summary of risks and vulnerabilities in large language models . it will also outline emerging challenges in security, privacy and reliability of LLMs . |
Explanation in the Era of Large Language Models (2024.naacl-tutorials)
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| Challenge: | Explanation has long been a part of communication, where humans use language to elucidate each other and transmit information about mechanisms of events. |
| Approach: | They review the opportunities and challenges of explanations in the era of large language models and examine how they can be used to generate explanations. |
| Outcome: | The proposed methods are based on the models of large language models (LLMs) and their opaque nature. |
From Text to Context: Contextualizing Language with Humans, Groups, and Communities for Socially Aware NLP (2024.naacl-tutorials)
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Adithya V Ganesan, Siddharth Mangalik, Vasudha Varadarajan, Nikita Soni, Swanie Juhng, João Sedoc, H. Andrew Schwartz, Salvatore Giorgi, Ryan L Boyd
| Challenge: | This tutorial will cover the latest techniques and libraries for doing so at each level of analysis. |
| Approach: | This tutorial will cover the latest techniques and libraries for doing so at each level of analysis. |
| Outcome: | The tutorial covers human-centered techniques that provide benefit to traditional document- or word-level NLP tasks. |
Human-AI Interaction in the Age of LLMs (2024.naacl-tutorials)
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| Challenge: | Large Language Models (LLMs) have revolutionized the capabilities of AI systems. |
| Approach: | This tutorial will provide an overview of the interaction between humans and Large Language Models (LLMs) it will start with a review of the types of AI models we interact with and walkthrough of the core concepts in Human-AI Interaction. |
| Outcome: | This tutorial will provide an overview of the interaction between humans and LLMs, exploring the challenges, opportunities, and ethical considerations that arise in this dynamic landscape. |
Spatial and Temporal Language Understanding: Representation, Reasoning, and Grounding (2024.naacl-tutorials)
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| Challenge: | This tutorial provides an overview of cutting edge research on spatial and temporal language understanding. |
| Approach: | This tutorial provides an overview of cutting edge research on spatial and temporal language understanding. |
| Outcome: | This tutorial provides an overview of cutting edge research on spatial and temporal language understanding. |