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Summary of Evaluating Llms Capabilities Towards Understanding Social Dynamics, by Anique Tahir et al.


Evaluating LLMs Capabilities Towards Understanding Social Dynamics

by Anique Tahir, Lu Cheng, Manuel Sandoval, Yasin N. Silva, Deborah L. Hall, Huan Liu

First submitted to arxiv on: 20 Nov 2024

Categories

  • Main: Machine Learning (cs.LG)
  • Secondary: Artificial Intelligence (cs.AI)

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GrooveSquid.com Paper Summaries

GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!

Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
Medium Difficulty summary: The paper explores the ability of generative large language models (LLMs) like Llama and ChatGPT to understand social media dynamics, particularly in contexts related to cyberbullying. It compares the performance of different LLMs in understanding language, directionality, and bullying/anti-bullying message detection. While fine-tuned LLMs show promise in some tasks, they exhibit mixed results in others. The study highlights the importance of understanding LLM capabilities for designing effective models that can be used in social applications. Key findings include the positive effects of fine-tuning and prompt engineering on certain tasks. Overall, this research is crucial for developing future LLMs that can effectively tackle complex social media issues.
Low GrooveSquid.com (original content) Low Difficulty Summary
Low Difficulty summary: This study looks at how well artificial intelligence (AI) language models can understand what’s happening on social media, especially when it comes to bullying. The researchers tested different AI models to see if they could understand things like who is saying what and whether messages are helpful or hurtful. While some models did better than others, the results show that these AI models still have a lot to learn about how people interact with each other online. This research is important because it can help us build better AI models that can help stop bullying on social media.

Keywords

» Artificial intelligence  » Fine tuning  » Llama  » Prompt