Emotions and AI

Source papers 34

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

• "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…
• Backtracing: Retrieving the Cause of the Query
  While information retrieval (IR) systems may provide answers for such user queries, they do not directly assist content creators—such as lecturers who want to improve their content—identify segments t…
• Chain of Stance: Stance Detection with Large Language Models
  Stance detection is an active task in natural language processing (NLP) that aims to identify the author’s stance towards a particular target within a text. Given the remarkable language understanding…
• ChatGPT Reads Your Tone and Responds Accordingly -- Until It Does Not -- Emotional Framing Induces Bias in LLM Outputs
  Background: Large Language Models (LLMs) like GPT-4 tailor their responses not just to the content but also to the tone of user prompts. Prior work has hinted that emotional phrasing – whether optimis…
• Comparing emotion feature extraction approaches for predicting depression and anxiety
  For example, pride may be impacted by depression in a unique way. Gruber et al. (2011) showed that pride, a positive emotion relating to the self, is inversely correlated with depression, which is oft…
• Consistently Simulating Human Personas with Multi-Turn Reinforcement Learning
  Large Language Models (LLMs) are increasingly used to simulate human users in interactive settings such as therapy, education, and social role-play. While these simulations enable scalable training an…
• DeepGesture: A conversational gesture synthesis system based on emotions and semantics
  Along with the explosion of large language models, improvements in speech synthesis, advancements in hardware, and the evolution of computer graphics, the current bottleneck in creating digital humans…
• 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 conten…
• Disambiguating Anthropomorphism and Anthropomimesis in Human-Robot Interaction
  Henry Shevlin [[Emotions]] [[Psychology Users]] [[Design Frameworks]] In this preliminary work, we offer an initial disambiguation of the theoretical concepts anthropomorphism and anthropomimesis in…
• EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus
  “Large language models (LLMs) have achieved significant performance in many fields, such as reasoning, language understanding, and math problem-solving, and are regarded as an important step to artifi…
• Evaluating Emotional Nuances In Dialogue Summarization
  Automatic dialogue summarization is a well-established task that aims to identify the most important content from human conversations to create a short textual summary. Despite recent progress in the …
• Evaluating the Efficacy of Interactive Language Therapy Based on LLM for High-Functioning Autistic Adolescent Psychological Counseling
  significant emphasis was placed on the development of prompts used to guide the Large LanguageModel (LLM). This process was intricate and involved multiple stages to ensure that the prompts were effec…
• Explainable Multimodal Emotion Reasoning
  Multimodal emotion recognition is an active research topic in the field of artificial intelligence. It aims to integrate multimodal clues (including acoustic, visual, and lexical clues) and recognize …
• Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers
  Should a large language model (LLM) be used as a therapist? In this paper, we investigate the use of LLMs to replace mental health providers, a use case promoted in the tech startup and research space…
• Forecasting the presence and intensity of hostility on Instagram using linguistic and social features
  Online antisocial behavior, such as cyberbullying, harassment, and trolling, is a widespread problem that threatens free discussion and has negative physical and mental health consequences for victims…
• 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 …
• H2HTalk: Evaluating Large Language Models as Emotional Companion
  We present Heart-to-Heart Talk (H2HTalk), a benchmark assessing companions across personality development and empathetic interaction, balancing emotional intelligence with linguistic fluency. H2HTalk …
• 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…
• 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…
• Knowledge-enhanced Mixed-initiative Dialogue System for Emotional Support Conversations
  Unlike empathetic dialogues, the system in emotional support conversations (ESC) is expected to not only convey empathy for comforting the help-seeker, but also proactively assist in exploring and add…
• LLM-based Conversational AI Therapist for Daily Functioning Screening and Psychotherapeutic Intervention via Everyday Smart Devices
  When the user needs further attention during the conversation, CaiTI can provide conversational psychotherapeutic interventions, including cognitive behavioral therapy (CBT) and motivational interview…
• 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…
• MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis
  The application of AI in psychiatric diagnosis faces significant challenges, including the subjective nature of mental health assessments, symptom overlap across disorders, and privacy constraints lim…
• 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…
• RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
  However, the exploration of RLVR for enhancing dialogue capabilities faces several key obstacles: • the lack of a stable, realistic, and scalable environment for multi-turn conversational rollouts; …
• Revolutionizing Mental Health Support: An Innovative Affective Mobile Framework for Dynamic, Proactive, and Context-Adaptive Conversational Agents
  As we build towards developing interactive systems that can recognize human emotional states and respond to individual needs more intuitively and empathetically in more personalized and context-aware …
• Study: Large language models can’t effectively recognize users’ motivation, but can support behavior change for those ready to act
  Chin said previous studies showed that existing algorithms did not accurately identify various stages of users’ motivation. She and Bak designed a study to test how well large language models, which a…
• The Emotion-Memory Link: Do Memorability Annotations Matter for Intelligent Systems?
  Abstract—Humans have a selective memory, remembering relevant episodes and forgetting the less relevant information. Possessing awareness of event memorability for a user could help intelligent system…
• 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…
• 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 Empathetic Open-domain Conversation Models: A New Benchmark and Dataset
  This work proposes a new benchmark for empathetic dialogue generation and EMPATHETICDIALOGUES, a novel dataset of 25k conversations grounded in emotional situations. Our experiments indicate that dial…
• 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…
• Word Meanings in Transformer Language Models
  We investigate how word meanings are represented in the transformer language models. Specifically, we focus on whether transformer models employ something analogous to a lexical store - where each wor…
• 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…