# MindTailor: Personalized Emotional Support via Post History-Grounded Case Formulation and Collaborative Refinement

arXiv: https://arxiv.org/abs/2606.21930 · HTML: https://mlsanity.com/paper/2606.21930/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 24 of its 64 references that are in the map.
- First posted on arXiv 20 Jun 2026.

## Builds on (most cited first, 24 of 24)

- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [Large Language Models are not Fair Evaluators](https://mlsanity.com/paper/2305.17926/) (2023)
- [DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence](https://mlsanity.com/paper/2606.19348/) (2026)
- [CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing](https://mlsanity.com/paper/2305.11738/) (2023)
- [GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models](https://mlsanity.com/paper/2508.06471/) (2025)
- [Towards Emotional Support Dialog Systems](https://mlsanity.com/paper/2106.01144/) (2021)
- [MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation](https://mlsanity.com/paper/2203.13560/) (2022)
- [Depression and Self-Harm Risk Assessment in Online Forums](https://mlsanity.com/paper/1709.01848/) (2017)
- [Understanding Iterative Revision from Human-Written Text](https://mlsanity.com/paper/2203.03802/) (2022)
- [PAL: Persona-Augmented Emotional Support Conversation Generation](https://mlsanity.com/paper/2212.09235/) (2022)
- [Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI](https://mlsanity.com/paper/2309.12444/) (2023)
- [TransESC: Smoothing Emotional Support Conversation via Turn-Level State Transition](https://mlsanity.com/paper/2305.03296/) (2023)
- [FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversation](https://mlsanity.com/paper/2211.00250/) (2022)
- [IntentionESC: An Intention-Centered Framework for Enhancing Emotional Support in Dialogue Systems](https://mlsanity.com/paper/2506.05947/) (2025)
- [RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses](https://mlsanity.com/paper/1806.07916/) (2018)
- [From Generic Empathy to Personalized Emotional Support: A Self-Evolution Framework for User Preference Alignment](https://mlsanity.com/paper/2505.16610/) (2025)
- [MentalAgora: A Gateway to Advanced Personalized Care in Mental Health through Multi-Agent Debating and Attribute Control](https://mlsanity.com/paper/2407.02736/) (2024)
- [Dialogue Systems for Emotional Support via Value Reinforcement](https://mlsanity.com/paper/2501.17182/) (2025)
- [AutoPal: Autonomous Adaptation to Users for Personal AI Companionship](https://mlsanity.com/paper/2406.13960/) (2024)
- [Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation](https://mlsanity.com/paper/2404.02505/) (2024)
- [CauESC: A Causal Aware Model for Emotional Support Conversation](https://mlsanity.com/paper/2401.17755/) (2024)
- [Persona Extraction Through Semantic Similarity for Emotional Support Conversation Generation](https://mlsanity.com/paper/2403.04212/) (2024)
- [GRAVITY: A Framework for Personalized Text Generation via Profile-Grounded Synthetic Preferences](https://mlsanity.com/paper/2510.11952/) (2025)

## Abstract (arXiv)

As mental health concerns continue to rise globally, social media has emerged as a vital space where individuals seek emotional support. While prior work on personalized emotional support has leveraged seekers' emotional states, personas, and situational context, these approaches primarily capture the seeker's current state, overlooking the formative experiences that shape present concerns. In this work, we propose MindTailor, a framework that generates personalized emotional support responses by constructing a case formulation from the seeker's post history and iteratively refining responses through collaborative critique among counselor agents grounded in distinct counseling strategies. To enable research on this history-aware task, we construct ReddiSupp, a dataset of 798 Reddit posts paired with seekers' prior post histories. Through LLM-as-a-Judge evaluation, expert human evaluation, and a user study with seekers, we demonstrate that MindTailor outperforms baselines across these evaluations, improving empathy, personalization, understanding, and achieving the highest overall preference.