@inproceedings{polignano-etal-2024-unraveling,
title = "Unraveling the Enigma of {SPLIT} in Large-Language Models: The Unforeseen Impact of System Prompts on {LLM}s with Dissociative Identity Disorder",
author = "Polignano, Marco and
De Gemmis, Marco and
Semeraro, Giovanni",
editor = "Dell'Orletta, Felice and
Lenci, Alessandro and
Montemagni, Simonetta and
Sprugnoli, Rachele",
booktitle = "Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)",
month = dec,
year = "2024",
address = "Pisa, Italy",
publisher = "CEUR Workshop Proceedings",
url = "https://aclanthology.org/2024.clicit-1.84/",
pages = "774--780",
ISBN = "979-12-210-7060-6",
abstract = "Our work delves into the unexplored territory of Large-Language Models (LLMs) and their interactions with System Prompts, unveiling the previously undiscovered implications of SPLIT (System Prompt Induced Linguistic Transmutation) in commonly used state-of-the-art LLMs. Dissociative Identity Disorder, a complex and multifaceted mental health condition, is characterized by the presence of two or more distinct identities or personas within an individual, often with varying levels of awareness and control. The advent of large-language models has raised intriguing questions about the presence of such conditions in LLMs. Our research investigates the phenomenon of SPLIT, in which the System Prompt, a seemingly innocuous input, profoundly impacts the linguistic outputs of LLMs. The findings of our study reveal a striking correlation between the System Prompt and the emergence of distinct, persona-like linguistic patterns in the LLM`s responses. These patterns are not only reminiscent of the dissociative identities present in the original data but also exhibit a level of coherence and consistency that is uncommon in typical LLM outputs. As we continue to explore the capabilities of LLMs, it is imperative that we maintain a keen awareness of the potential for SPLIT and its significant implications for the development of more human-like and empathetic AI systems."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="polignano-etal-2024-unraveling">
<titleInfo>
<title>Unraveling the Enigma of SPLIT in Large-Language Models: The Unforeseen Impact of System Prompts on LLMs with Dissociative Identity Disorder</title>
</titleInfo>
<name type="personal">
<namePart type="given">Marco</namePart>
<namePart type="family">Polignano</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marco</namePart>
<namePart type="family">De Gemmis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Giovanni</namePart>
<namePart type="family">Semeraro</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Felice</namePart>
<namePart type="family">Dell’Orletta</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Lenci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Simonetta</namePart>
<namePart type="family">Montemagni</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rachele</namePart>
<namePart type="family">Sprugnoli</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>CEUR Workshop Proceedings</publisher>
<place>
<placeTerm type="text">Pisa, Italy</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-12-210-7060-6</identifier>
</relatedItem>
<abstract>Our work delves into the unexplored territory of Large-Language Models (LLMs) and their interactions with System Prompts, unveiling the previously undiscovered implications of SPLIT (System Prompt Induced Linguistic Transmutation) in commonly used state-of-the-art LLMs. Dissociative Identity Disorder, a complex and multifaceted mental health condition, is characterized by the presence of two or more distinct identities or personas within an individual, often with varying levels of awareness and control. The advent of large-language models has raised intriguing questions about the presence of such conditions in LLMs. Our research investigates the phenomenon of SPLIT, in which the System Prompt, a seemingly innocuous input, profoundly impacts the linguistic outputs of LLMs. The findings of our study reveal a striking correlation between the System Prompt and the emergence of distinct, persona-like linguistic patterns in the LLM‘s responses. These patterns are not only reminiscent of the dissociative identities present in the original data but also exhibit a level of coherence and consistency that is uncommon in typical LLM outputs. As we continue to explore the capabilities of LLMs, it is imperative that we maintain a keen awareness of the potential for SPLIT and its significant implications for the development of more human-like and empathetic AI systems.</abstract>
<identifier type="citekey">polignano-etal-2024-unraveling</identifier>
<location>
<url>https://aclanthology.org/2024.clicit-1.84/</url>
</location>
<part>
<date>2024-12</date>
<extent unit="page">
<start>774</start>
<end>780</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Unraveling the Enigma of SPLIT in Large-Language Models: The Unforeseen Impact of System Prompts on LLMs with Dissociative Identity Disorder
%A Polignano, Marco
%A De Gemmis, Marco
%A Semeraro, Giovanni
%Y Dell’Orletta, Felice
%Y Lenci, Alessandro
%Y Montemagni, Simonetta
%Y Sprugnoli, Rachele
%S Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)
%D 2024
%8 December
%I CEUR Workshop Proceedings
%C Pisa, Italy
%@ 979-12-210-7060-6
%F polignano-etal-2024-unraveling
%X Our work delves into the unexplored territory of Large-Language Models (LLMs) and their interactions with System Prompts, unveiling the previously undiscovered implications of SPLIT (System Prompt Induced Linguistic Transmutation) in commonly used state-of-the-art LLMs. Dissociative Identity Disorder, a complex and multifaceted mental health condition, is characterized by the presence of two or more distinct identities or personas within an individual, often with varying levels of awareness and control. The advent of large-language models has raised intriguing questions about the presence of such conditions in LLMs. Our research investigates the phenomenon of SPLIT, in which the System Prompt, a seemingly innocuous input, profoundly impacts the linguistic outputs of LLMs. The findings of our study reveal a striking correlation between the System Prompt and the emergence of distinct, persona-like linguistic patterns in the LLM‘s responses. These patterns are not only reminiscent of the dissociative identities present in the original data but also exhibit a level of coherence and consistency that is uncommon in typical LLM outputs. As we continue to explore the capabilities of LLMs, it is imperative that we maintain a keen awareness of the potential for SPLIT and its significant implications for the development of more human-like and empathetic AI systems.
%U https://aclanthology.org/2024.clicit-1.84/
%P 774-780
Markdown (Informal)
[Unraveling the Enigma of SPLIT in Large-Language Models: The Unforeseen Impact of System Prompts on LLMs with Dissociative Identity Disorder](https://aclanthology.org/2024.clicit-1.84/) (Polignano et al., CLiC-it 2024)
ACL