Personas and Personality

Source papers 62

The Arxiv papers behind this sub-topic. Links may take you off-site to arxiv.org.

• Assessment of Personality Dimensions Across Situations Using Conversational Speech
  Abstract—Prior research indicates that users prefer assistive technologies whose personalities align with their own. This has sparked interest in automatic personality perception (APP), which aims to …
• Beyond Discrete Personas: Personality Modeling Through Journal Intensive Conversations
  Large Language Models (LLMs) have significantly improved personalized conversational capabilities. However, existing datasets like Persona Chat, Synthetic Persona Chat, and Blended Skill Talk rely on …
• Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning
  Maintaining a consistent persona is a key quality for any open domain dialogue system. Current state-of-the-art systems do this by training agents with supervised learning or online reinforcement lear…
• Can AI Have a Personality? Prompt Engineering for AI Personality Simulation: A Chatbot Case Study in Gender-Affirming Voice Therapy Training
  Abstract—This thesis investigates whether large language models (LLMs) can be guided to simulate a consistent personality through prompt engineering. The study explores this concept within the context…
• Can LLM be a Personalized Judge?
  Ensuring that large language models (LLMs) reflect diverse user values and preferences is crucial as their user bases expand globally. It is therefore encouraging to see the growing interest in LLM pe…
• Chamain: Harmonizing Character Persona Integrity with Domain-Adaptive Knowledge in Dialogue Generation
  Recent advances in large language models (LLMs) have shown their capacity for generating natural dialogues, leveraging extensive pre-trained knowledge. However, the seamless integration of domain-spec…
• Character is Destiny: Can Role-Playing Language Agents Make Persona-Driven Decisions?
  Can Large Language Models (LLMs) simulate humans in making important decisions? Recent research has unveiled the potential of using LLMs to develop role-playing language agents (RPLAs), mimicking main…
• CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models
   Large language models (LLMs) have facilitated significant strides in generating conversational agents, enabl…
• Cognitive Effects in Large Language Models
  Abstract. Large Language Models (LLMs) such as ChatGPT have received enormous attention over the past year and are now used by hundreds of millions of people every day. The rapid adoption of this tech…
• Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design
  In the rapidly evolving field of artificial intelligence (AI) agents, designing the agent’s characteristics is crucial for shaping user experience. This workshop aims to establish a research community…
• Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language Models
    The field of large language models (LLMs…
• Do Theory of Mind Benchmarks Need Explicit Human-like Reasoning in Language Models?
  Recent advancements in Large Language Models (LLMs) have shown promising performance on ToM benchmarks, raising the question: Do these benchmarks necessitate explicit human-like reasoning processes, o…
• From Five Dimensions to Many: Large Language Models as Precise and Interpretable Psychological Profilers
  We prompted various LLMs with Big Five Personality Scale responses from 816 human individuals to role-play their responses on nine other psychological scales. LLMs demonstrated remarkable accuracy in …
• From Persona to Person: Enhancing the Naturalness with Multiple Discourse Relations Graph Learning in Personalized Dialogue Generation
  Abstract. In dialogue generation, the naturalness of responses is crucial for effective human-machine interaction. Personalized response generation poses even greater challenges, as the responses must…
• From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs
  we employed Opinion QA Based Parameter-Efficient Fine- Tuning (PEFT), specifically Quantized Low- Rank Adaptation (QLoRA), to manipulate the Big Five personality traits: Openness, Conscientiousness, E…
• Generating Proto-Personas through Prompt Engineering: A Case Study on Efficiency, Effectiveness and Empathy
  In this paper, we propose and empirically investigate a prompt engineering-based approach to generate proto-personas with the support of Generative AI (GenAI). Our goal is to evaluate the approach in …
• Generative Agent Simulations of 1,000 People
  We present a novel agent architecture that simulates the attitudes and behaviors of 1,052 real individuals—applying large language models to qualitative interviews about their lives, then measuring ho…
• Improving Dialog Systems for Negotiation with Personality Modeling
  In this paper, we explore the ability to model and infer personality types of opponents, predict their responses, and use this information to adapt a dialog agent’s high-level strategy in negotiation …
• InMind: Evaluating LLMs in Capturing and Applying Individual Human Reasoning Styles
  LLMs have shown strong performance on human-centric reasoning tasks. While previous evaluations have explored whether LLMs can infer intentions or detect deception, they often overlook the individuali…
• Inspecting and Editing Knowledge Representations in Language Models
  Neural language models (LMs) represent facts about the world described by text. Sometimes these facts derive from training data (in most LMs, a representation of the word banana encodes the fact that …
• LLM Generated Persona is a Promise with a Catch
  The use of large language models (LLMs) to simulate human behavior has gained significant attention, particularly through personas that approximate individual characteristics. Persona-based simulation…
• LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings
  Consumer research costs companies billions annually yet suffers from panel biases and limited scale. Large language models (LLMs) offer an alternative by simulating synthetic consumers, but produce un…
• Large Language Models Can Infer Psychological Dispositions of Social Media Users
  Large Language Models (LLMs) demonstrate increasingly human-like abilities across a wide variety of tasks. In this paper, we investigate whether LLMs like ChatGPT can accurately infer the psychologica…
• Large Language Models Do Not Simulate Human Psychology
  In response to the LLM CENTAUR [Binz et al., 2025], Bowers et al. [2025] argued that CENTAUR is unlikely to contribute to building a theory of human cognition for three reasons: First, CENTAUR was not…
• Measuring and Mitigating Persona Distortions from AI Writing Assistance
  Hundreds of millions of people use artificial intelligence (AI) for writing assistance. Here, we evaluated how AI writing assistance distorts writer personas – their perceived beliefs, personality, an…
• On The Persona-based Summarization of Domain-Specific Documents
  In an ever-expanding world of domain-specific knowledge, the increasing complexity of consuming, and storing information necessitates the generation of summaries from large information repositories. H…
• On the Adaptive Psychological Persuasion of Large Language Models
  However, systematic exploration of their dual capabilities to autonomously persuade and resist persuasion, particularly in contexts involving psychological rhetoric, remains unexplored. In this paper,…
• Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Models
  Our approach involves evaluating the intrinsic personality traits of Open LLM agents and determining the extent to which these agents can mimic human personalities when conditioned by specific persona…
• PersLLM: A Personified Training Approach for Large Language Models
  Large language models (LLMs) exhibit humanlike intelligence, enabling them to simulate human behavior and support various applications that require both humanized communication and extensive knowledge…
• Persona Generators: Generating Diverse Synthetic Personas at Scale
  Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative human data is often expensive or infeasible, partic…
• Persona Vectors: Monitoring and Controlling Character Traits in Language Models
  Large language models interact with users through a simulated “Assistant” persona. While the Assistant is typically trained to be helpful, harmless, and honest, it sometimes deviates from these ideals…
• Persona-Assigned Large Language Models Exhibit Human-Like Motivated Reasoning
  (LLMs) are also susceptible to human-like cognitive biases, however, the extent to which LLMs selectively reason toward identity-congruent conclusions remains largely unexplored. Here, we investigate …
• PersonaAgent: When Large Language Model Agents Meet Personalization at Test Time
  This limitation motivates us to develop PersonaAgent, the first personalized LLM agent framework designed to address versatile personalization tasks. Specifically, PersonaAgent integrates two compleme…
• PersonaGym: Evaluating Persona Agents and LLMs
   Persona agents, which are LLM agents that act according to an assigned persona, have demonstrated impressi…
• PersonaPKT: Building Personalized Dialogue Agents via Parameter-efficient Knowledge Transfer
  “Personalized dialogue agents (DAs) powered by large pre-trained language models (PLMs) often rely on explicit persona descriptions to maintain personality consistency. However, such descriptions may …
• Personalization of Large Language Models: A Survey
  Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on persona…
• PersuasiveToM: A Benchmark for Evaluating Machine Theory of Mind in Persuasive Dialogues
  The ability to understand and predict the mental states of oneself and others, known as the Theory of Mind (ToM), is crucial for effective social scenarios. Although recent studies have evaluated ToM …
• PosterMate: Audience-driven Collaborative Persona Agents for Poster Design
  PosterMate gathers feedback from each persona agent regarding poster components, and stimulates discussion with the help of a moderator to reach a conclusion. These agreed-upon edits can then be direc…
• Prompting Science Report 4: Playing Pretend: Expert Personas Don't Improve Factual Accuracy
  Summary This is the fourth in a series of short reports that help business, education, and policy leaders understand the technical details of working with AI through rigorous testing. Here, we ask whe…
• Proxona: Leveraging LLM-Driven Personas to Enhance Creators' Understanding of Their Audience
  we present Proxona, a system for defining and extracting representative audience personas from the comments. Creators converse with personas to gain insights into their preferences and engagement, sol…
• PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling
  Currently, large language models (LLMs) have made significant progress in the field of psychological counseling. However, existing mental health LLMs overlook a critical issue where they do not consid…
• PsychAdapter: Adapting LLM Transformers to Reflect Traits, Personality and Mental Health
  Artificial intelligence-based language generators are now a part of most people’s lives. However, by default, they tend to generate “average” language without reflecting the ways in which people diffe…
• Psychologically Enhanced AI Agents
  We introduce MBTI-in-Thoughts, a framework for enhancing the effectiveness of Large Language Model (LLM) agents through psychologically grounded personality conditioning. Drawing on the Myers–Briggs T…
• Recent Trends in Personalized Dialogue Generation: A Review of Datasets, Methodologies, and Evaluations
  Enhancing user engagement through personalization in conversational agents has gained significance, especially with the advent of large language models that generate fluent responses. Personalized dia…
• Role play with large language models
  Here we advocate two basic metaphors for LLM-based dialogue agents. First, taking a simple and intuitive view, we can see a dialogue agent as role-playing a single character. Second, taking a more nua…
• RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models
  However, the closed-source nature of state-of-the-art LLMs and their general-purpose training limit role-playing optimization. In this paper, we introduce RoleLLM, a framework to benchmark, elicit, an…
• Scaling Synthetic Data Creation with 1,000,000,000 Personas
   We propose a novel persona-driven data synthesis methodology that leverages various perspectives within a large language m…
• Systematic synthesis of design prompts for large language models in conceptual design
  Conceptual design can be modeled as a proposition making process, where designers make logical propositions to communicate and construct intangible concepts. Not only can LLMs interpret designers’ pro…
• Tell me about yourself: LLMs are aware of their learned behaviors
  We study behavioral self-awareness — an LLM’s ability to articulate its behaviors without requiring in-context examples. We finetune LLMs on datasets that exhibit particular behaviors, such as (a) mak…
• The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models
  Large language models can represent a variety of personas but typically default to a helpful Assistant identity cultivated during post-training. We investigate the structure of the space of model pers…
• The Incomplete Bridge: How AI Research (Mis)Engages with Psychology
  Social sciences have accumulated a rich body of theories and methodologies for investigating the human mind and behaviors, while offering valuable insights into the design and understanding of Artific…
• Think Like a Person Before Responding: A Multi-Faceted Evaluation of Persona-Guided LLMs for Countering Hate
  Automated counter-narratives (CN) offer a promising strategy for mitigating online hate speech, yet concerns about their affective tone, accessibility and ethical risks remain. We propose a framework …
• Thinking Assistants: LLM-Based Conversational Assistants that Help Users Think By Asking rather than Answering
  complex tasks like research and strategic thinking often benefit from a more comprehensive approach to augmenting the thinking process rather than passively getting information. We introduce the conce…
• Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning
  The advancement of Large Language Models (LLMs) has spurred significant interest in Role-Playing Agents (RPAs) for applications such as emotional companionship and virtual interaction. However, recent…
• Too Good to be Bad: On the Failure of LLMs to Role-Play Villains
  Large Language Models (LLMs) are increasingly tasked with creative generation, including the simulation of fictional characters. However, their ability to portray non-prosocial, antagonistic personas …
• Training a Generally Curious Agent
  Efficient exploration is essential for intelligent systems interacting with their environment, but existing language models often fall short in scenarios that require strategic information gathering. …
• Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization
  The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., personalized search, LLM…
• Unleashing Cognitive Synergy In Large Language Models: A Task-solving Agent Through Multi-persona Self-collaboration
  “A cognitive synergist denotes an intelligent agent that works in conjunction with several minds, merging their unique abilities and expertise to improve problem-solving and overall efficacy in intric…
• Unlocking Varied Perspectives: A Persona-Based Multi-Agent Framework with Debate-Driven Text Planning for Argument Generation
  Writing persuasive arguments is a challenging task for both humans and machines. It entails incorporating high-level beliefs from various perspectives on the topic, along with deliberate reasoning and…
• Using Large Language Models to Create AI Personas for Replication and Prediction of Media Effects: An Empirical Test of 133 Published Experimental Research Findings
  Our LLM replications successfully reproduced 76% of the original main effects (84 out of 111), demonstrating strong potential for AI-assisted replication of studies in which people respond to media st…
• What we talk to when we talk to language models
  David Chalmers [[Linguistics, NLP, NLU]] [[Role Play]] [[Philosophy Subjectivity]] Quasi-interpretivism does not say anything about whether LLMs have beliefs and desires. But it does make it plausib…
• Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness
  We explore the task of improving persona consistency of dialogue agents. Recent models tackling consistency often train with additional Natural Language Inference (NLI) labels or attach trained extra …