Chatbot Psychology and Conversation

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• "My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community
  The emergence of AI companion applications has created novel forms of intimate human-AI relationships, yet empirical research on these communities remains limited. We present the first large-scale com…
• A Computational Framework for Behavioral Assessment of LLM Therapists
  we propose BOLT, a novel computational framework to study the conversational behavior of LLMs when employed as therapists. We develop an in-context learning method to quantitatively measure the behavi…
• 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 robots do therapy?: Examining the efficacy of a CBT bot in comparison with other behavioral intervention technologies in alleviating mental health symptoms
  In a recent systematic review of the literature, (Conley et al., 2022) note that this literature has yet to answer the question of whether BITs can be considered an effective and low-cost substitution…
• CogBench: a large language model walks into a psychology lab
  CogBench, a benchmark that includes ten behavioral metrics derived from seven cognitive psychology experiments. This novel approach offers a toolkit for phenotyping LLMs’ behavior. We apply CogBench t…
• Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot’s Self-Disclosure in Conversational Recommendations
  “Using chatbots to deliver recommendations is increasingly popular. The design of recommendation chatbots has primarily been taking an information-centric approach by focusing on the recommended conte…
• DiscussLLM: Teaching Large Language Models When to Speak
  Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as reactive agents, responding only when directly promp…
• 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…
• Evidence of Human-Level Bonds Established With a Digital Conversational Agent: Cross-sectional, Retrospective Observational Study
  We aimed to investigate whether users of a cognitive behavioral therapy (CBT)–based conversational agent would report therapeutic bond levels that are similar to those in literature about other CBT mo…
• From speaking like a person to being personal: The effects of personalized, regular interactions with conversational agents
  human-AI interactions (Sundar, 2020). Interactions with these agents may have a shorter-term, transactional nature, for example checking the status of an order with a customer service chatbot, or a lo…
• GenAI as a Power Persuader: How Professionals Get Persuasion Bombed When They Attempt to Validate LLMs
  When diligent professionals make decisions, they validate their analyses. Increasingly, professionals across domains use generative AI (GenAI) for analytic knowledge work and therefore validate the AI…
• Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models
  Existing LLM reasoning methods have shown impressive capabilities across various tasks, such as solving math and coding problems. However, applying these methods to scenarios without ground-truth answ…
• IMBUE: Improving Interpersonal Effectiveness through Simulation and Just-in-time Feedback with Human-Language Model Interaction
  Navigating certain communication situations can be challenging due to individuals’ lack of skills and the interference of strong emotions. However, effective learning opportunities are rarely accessib…
• 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…
• Interaction Dynamics as a Reward Signal for LLMs
  The alignment of Large Language Models (LLMs) for multi-turn conversations typically relies on reward signals derived from the content of the text. This approach, however, overlooks a rich, complement…
• LLM-based Conversational AI Therapist for Daily Functioning Screening and Psychotherapeutic Intervention via Everyday Smart Devices
  Description automatically generated](file:////Users/adrianchan/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image011.png) When the user needs further attention during …
• Large Language Models are as persuasive as humans, but how? About the cognitive effort and moral-emotional language of LLM arguments
  Abstract. Large Language Models (LLMs) are already as persuasive as humans. However, we know very little about how they do it. This paper investigates the persuasion strategies of LLMs, comparing them…
• Learning "Partner-Aware" Collaborators in Multi-Party Collaboration
  Large Language Models (LLMs) are increasingly bring deployed in agentic settings where they act as collaborators with humans. Therefore, it is increasingly important to be able to evaluate their abili…
• Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover's Distance
  Linguistic coordination is a well-established phenomenon in spoken conversations and often associated with positive social behaviors and outcomes. While there have been many attempts to measure lexica…
• 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 …
• Proactive Conversational Agents with Inner Thoughts
  In this paper, we demonstrate the limitations of such methods and rethink what it means for AI to be proactive in multi-party, human-AI conversations. We propose that just like humans, rather than mer…
• PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counseling
  LLMs fail to satisfy the individual needs of clients who seek different counseling styles. To help bridge this gap, we propose PsyDT, a novel framework using LLMs to construct the Digital Twin of Psyc…
• Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot
  identity of a conversation partner, as a human or computer, matters. Previous work has found that the mere perceived identity of the partner as computer or human has profound effects, even when actual…
• Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot
  identity of a conversation partner, as a human or computer, matters. Previous work has found that the mere perceived identity of the partner as computer or human has profound effects, even when actual…
• Quantifying Human-AI Synergy
  We introduce a novel Bayesian Item Response Theory framework to quantify human– AI synergy, separating individual and collaborative ability while controlling for task difficulty in interactive setting…
• Revolutionizing Mental Health Support: An Innovative Affective Mobile Framework for Dynamic, Proactive, and Context-Adaptive Conversational Agents
  BUILDING A CONTEXT-ADAPTIVE CHATBOT SYSTEM Our goal for this proposal is to discuss an exploration of the feasibility of building a chatbot system that integrates affective computing and language mod…
• Supporting Physical Activity Behavior Change with LLM-Based Conversational Agents
  Description automatically generated](file:////Users/adrianchan/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image003.png) Through formative interviews with 12 health p…
• The Challenges in Designing a Prevention Chatbot for Eating Disorders: Observational Study
  Background: Chatbots have the potential to provide cost-effective mental health prevention programs at scale and increase interactivity, ease of use, and accessibility of intervention programs. Objec…
• The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows
  The rapid integration of large language models (LLMs) into everyday workflows has transformed how individuals perform cognitive tasks such as writing, programming, analysis, and multilingual communica…
• The Partner Modelling Questionnaire: A validated self-report measure of perceptions toward machines as dialogue partners
  “The basic tenet of partner modelling is that people form a mental representation of their dialogue partner as a communicative and social entity [13, 30]. Originating in psycholinguistics, the concept…
• 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…
• Towards Healthy AI: Large Language Models Need Therapists Too
  Recent advances in large language models (LLMs) have led to the development of powerful AI chatbots capable of engaging in natural and human-like conversations. However, these chatbots can be potentia…
• Turn-taking and Backchannel Prediction with Acoustic and Large Language Model Fusion
  We propose an approach for continuous prediction of turn-taking and backchanneling locations in spoken dialogue by fusing a neural acoustic model with a large language model (LLM). Experiments on the …
• Understanding the Therapeutic Relationship between Counselors and Clients in Online Text-based Counseling using LLMs
  Robust therapeutic relationships between counselors and clients are fundamental to counseling effectiveness. The assessment of therapeutic alliance is well-established in traditional face-to-face ther…
• VCounselor: A Psychological Intervention Chat Agent Based on a Knowledge-Enhanced Large Language Model
  In the course of its work, the client's speeches are consolidated into a case, which is integrated into the structured input of the LLM together with dynamically changing additional material, and fina…
• Working Alliance Transformer for Psychotherapy Dialogue Classification
  As a predictive measure of the treatment outcome in psychotherapy, the working alliance measures the agreement of the patient and the therapist in terms of their bond, task and goal. Long been a clini…