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Computer Science > Computation and Language

arXiv:2406.05587 (cs)
[Submitted on 8 Jun 2024]

Title:Creativity Has Left the Chat: The Price of Debiasing Language
Models

Authors:Behnam Mohammadi
View a PDF of the paper titled Creativity Has Left the Chat: The
Price of Debiasing Language Models, by Behnam Mohammadi
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    Abstract:Large Language Models (LLMs) have revolutionized natural
    language processing but can exhibit biases and may generate toxic
    content. While alignment techniques like Reinforcement Learning
    from Human Feedback (RLHF) reduce these issues, their impact on
    creativity, defined as syntactic and semantic diversity, remains
    unexplored. We investigate the unintended consequences of RLHF on
    the creativity of LLMs through three experiments focusing on the
    Llama-2 series. Our findings reveal that aligned models exhibit
    lower entropy in token predictions, form distinct clusters in the
    embedding space, and gravitate towards "attractor states",
    indicating limited output diversity. Our findings have
    significant implications for marketers who rely on LLMs for
    creative tasks such as copywriting, ad creation, and customer
    persona generation. The trade-off between consistency and
    creativity in aligned models should be carefully considered when
    selecting the appropriate model for a given application. We also
    discuss the importance of prompt engineering in harnessing the
    creative potential of base models.

Subjects: Computation and Language (cs.CL); Artificial Intelligence
          (cs.AI)
Cite as:  arXiv:2406.05587 [cs.CL]
          (or arXiv:2406.05587v1 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2406.05587
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Behnam Mohammadi [view email]
[v1] Sat, 8 Jun 2024 22:14:51 UTC (7,925 KB)
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