# ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events

arXiv: https://arxiv.org/abs/2309.12244 · HTML: https://mlsanity.com/paper/2309.12244/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 100 references that are in the map.
- First posted on arXiv 21 Sep 2023.

## Builds on (most cited first, 18 of 18)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [PaLM: Scaling Language Modeling with Pathways](https://mlsanity.com/paper/2204.02311/) (2022)
- [A Survey of Large Language Models](https://mlsanity.com/paper/2303.18223/) (2023)
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://mlsanity.com/paper/2107.13586/) (2021)
- [LaMDA: Language Models for Dialog Applications](https://mlsanity.com/paper/2201.08239/) (2022)
- [BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset](https://mlsanity.com/paper/2307.04657/) (2023)
- [AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts](https://mlsanity.com/paper/2110.01691/) (2021)
- [Language Model Tokenizers Introduce Unfairness Between Languages](https://mlsanity.com/paper/2305.15425/) (2023)
- [Challenges in Building Intelligent Open-domain Dialog Systems](https://mlsanity.com/paper/1905.05709/) (2019)
- [To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making](https://mlsanity.com/paper/2102.09692/) (2021)
- [What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers](https://mlsanity.com/paper/2109.04650/) (2021)
- [Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data](https://mlsanity.com/paper/2301.05843/) (2023)
- [LLM-empowered Chatbots for Psychiatrist and Patient Simulation: Application and Evaluation](https://mlsanity.com/paper/2305.13614/) (2023)
- [Getting To Know You: User Attribute Extraction from Dialogues](https://mlsanity.com/paper/1908.04621/) (2019)
- [Towards an Online Empathetic Chatbot with Emotion Causes](https://mlsanity.com/paper/2105.11903/) (2021)
- [Anthropomorphization of AI: Opportunities and Risks](https://mlsanity.com/paper/2305.14784/) (2023)

## Built on by (most cited first, 30 of 31)

- [MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling](https://mlsanity.com/paper/2310.05231/) (2023)
- [MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation](https://mlsanity.com/paper/2502.11903/) (2025)
- [The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support](https://mlsanity.com/paper/2401.14362/) (2024)
- [Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation](https://mlsanity.com/paper/2502.02780/) (2025)
- [Not Just Novelty: A Longitudinal Study on Utility and Customization of an AI Workflow](https://mlsanity.com/paper/2402.09894/) (2024)
- [Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives](https://mlsanity.com/paper/2507.15783/) (2025)
- [Large Language Models for Subjective Language Understanding: A Survey](https://mlsanity.com/paper/2508.07959/) (2025)
- [KidLM: Advancing Language Models for Children -- Early Insights and Future Directions](https://mlsanity.com/paper/2410.03884/) (2024)
- [AACessTalk: Fostering Communication between Minimally Verbal Autistic Children and Parents with Contextual Guidance and Card Recommendation](https://mlsanity.com/paper/2409.09641/) (2024)
- [Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction](https://mlsanity.com/paper/2412.09318/) (2024)
- [The Impact of a Chatbot's Ephemerality-Framing on Self-Disclosure Perceptions](https://mlsanity.com/paper/2505.20464/) (2025)
- [ExploreSelf: Fostering User-driven Exploration and Reflection on Personal Challenges with Adaptive Guidance by Large Language Models](https://mlsanity.com/paper/2409.09662/) (2024)
- [LLM Safety for Children](https://mlsanity.com/paper/2502.12552/) (2025)
- [AI-Enabled Conversational Journaling for Advancing Parkinson's Disease Symptom Tracking](https://mlsanity.com/paper/2503.03532/) (2025)
- [ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations](https://mlsanity.com/paper/2506.14200/) (2025)
- [Helpful or Harmful? Exploring the Efficacy of Large Language Models for Online Grooming Prevention](https://mlsanity.com/paper/2403.09795/) (2024)
- [The Interaction Layer: An Exploration for Co-Designing User-LLM Interactions in Parental Wellbeing Support Systems](https://mlsanity.com/paper/2411.01228/) (2024)
- [EduAdapt: A Question Answer Benchmark Dataset for Evaluating Grade-Level Adaptability in LLMs](https://mlsanity.com/paper/2510.17389/) (2025)
- [The Role of Generative AI in Facilitating Social Interactions: A Scoping Review](https://mlsanity.com/paper/2506.10927/) (2025)
- [DinoCompanion: An Attachment-Theory Informed Multimodal Robot for Emotionally Responsive Child-AI Interaction](https://mlsanity.com/paper/2506.12486/) (2025)
- [Psychologically Enhanced AI Agents](https://mlsanity.com/paper/2509.04343/) (2025)
- [Chaplains' Reflections on the Design and Usage of AI for Conversational Care](https://mlsanity.com/paper/2602.04017/) (2026)
- [ChildEval: When large language models meet children's personalities](https://mlsanity.com/paper/2605.27805/) (2026)
- [The Nexus of AR/VR, AI, UI/UX, and Robotics Technologies in Enhancing Learning and Social Interaction for Children with Autism Spectrum Disorders: A Systematic Review](https://mlsanity.com/paper/2409.18162/) (2024)
- [Exploring the Innovation Opportunities for Pre-trained Models](https://mlsanity.com/paper/2505.15790/) (2025)
- [Autiverse: Eliciting Autistic Adolescents' Daily Narratives through AI-guided Multimodal Journaling](https://mlsanity.com/paper/2509.17466/) (2025)
- [Lived Experience in Dialogue: Co-designing Personalization in Large Language Models to Support Youth Mental Well-being](https://mlsanity.com/paper/2511.05769/) (2025)
- [Hybrid LLM-Embedded Dialogue Agents for Learner Reflection: Designing Responsive and Theory-Driven Interactions](https://mlsanity.com/paper/2602.20486/) (2026)
- [Structure Matters: Evaluating Multi-Agents Orchestration in Generative Therapeutic Chatbots](https://mlsanity.com/paper/2603.00774/) (2026)
- [Beyond "I Can't Help With That": How Child Safety Experts Evaluate AI Chatbot Safety](https://mlsanity.com/paper/2608.07902/) (2026)

## Abstract (arXiv)

Children typically learn to identify and express emotions through sharing their stories and feelings with others, particularly their family. However, it is challenging for parents or siblings to have emotional communication with children since children are still developing their communication skills. We present ChaCha, a chatbot that encourages and guides children to share personal events and associated emotions. ChaCha combines a state machine and large language models (LLMs) to keep the dialogue on track while carrying on free-form conversations. Through an exploratory study with 20 children (aged 8-12), we examine how ChaCha prompts children to share personal events and guides them to describe associated emotions. Participants perceived ChaCha as a close friend and shared their stories on various topics, such as family trips and personal achievements. Based on the findings, we discuss opportunities for leveraging LLMs to design child-friendly chatbots to support children in sharing emotions.