# Dialogue Systems for Emotional Support via Value Reinforcement

arXiv: https://arxiv.org/abs/2501.17182 · HTML: https://mlsanity.com/paper/2501.17182/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 47 references that are in the map.
- First posted on arXiv 25 Jan 2025.

## Builds on (most cited first, 15 of 15)

- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [Large Language Models](https://mlsanity.com/paper/2307.05782/) (2023)
- [Towards Emotional Support Dialog Systems](https://mlsanity.com/paper/2106.01144/) (2021)
- [Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents](https://mlsanity.com/paper/2311.00262/) (2023)
- [EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis](https://mlsanity.com/paper/2401.08508/) (2024)
- [Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning](https://mlsanity.com/paper/2210.04242/) (2022)
- [Cactus: Towards Psychological Counseling Conversations using Cognitive Behavioral Theory](https://mlsanity.com/paper/2407.03103/) (2024)
- [Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values](https://mlsanity.com/paper/2311.10766/) (2023)
- [ESCoT: Towards Interpretable Emotional Support Dialogue Systems](https://mlsanity.com/paper/2406.10960/) (2024)
- [PAL: Persona-Augmented Emotional Support Conversation Generation](https://mlsanity.com/paper/2212.09235/) (2022)
- [Ask an Expert: Leveraging Language Models to Improve Strategic Reasoning in Goal-Oriented Dialogue Models](https://mlsanity.com/paper/2305.17878/) (2023)
- [Generating Empathetic Responses by Looking Ahead the User's Sentiment](https://mlsanity.com/paper/1906.08487/) (2019)
- [Do Differences in Values Influence Disagreements in Online Discussions?](https://mlsanity.com/paper/2310.15757/) (2023)
- [Adam-Smith at SemEval-2023 Task 4: Discovering Human Values in Arguments with Ensembles of Transformer-based Models](https://mlsanity.com/paper/2305.08625/) (2023)
- [K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning](https://mlsanity.com/paper/2312.10371/) (2023)

## Built on by (most cited first, 8 of 8)

- [Affective Flow Language Model for Emotional Support Conversation](https://mlsanity.com/paper/2602.08826/) (2026)
- [Act-Adaptive Margin: Dynamically Calibrating Reward Models for Subjective Ambiguity](https://mlsanity.com/paper/2505.23923/) (2025)
- [Responsible Evaluation of AI for Mental Health](https://mlsanity.com/paper/2602.00065/) (2026)
- [Stress-Testing Emotional Support Models: Moving from Homogeneous to Diverse Help Seekers](https://mlsanity.com/paper/2601.07698/) (2026)
- [Listening to the Echo: User-Reaction Aware Policy Optimization via Scalar-Verbal Hybrid Reinforcement Learning](https://mlsanity.com/paper/2603.15434/) (2026)
- [Discourse Diversity in Multi-Turn Empathic Dialogue](https://mlsanity.com/paper/2604.11742/) (2026)
- [Discourse Coherence and Response-Guided Context Rewriting for Multi-Party Dialogue Generation](https://mlsanity.com/paper/2604.06784/) (2026)
- [MindTailor: Personalized Emotional Support via Post History-Grounded Case Formulation and Collaborative Refinement](https://mlsanity.com/paper/2606.21930/) (2026)

## Abstract (arXiv)

Emotional support dialogue systems aim to reduce help-seekers' distress and help them overcome challenges. While human valuesunicodex2013core beliefs that shape an individual's prioritiesunicodex2013are increasingly emphasized in contemporary psychological therapy for their role in fostering internal transformation and long-term emotional well-being, their integration into emotional support systems remains underexplored. To bridge this gap, we present a value-driven method for training emotional support dialogue systems designed to reinforce positive values in seekers. Notably, our model identifies which values to reinforce at each turn and how to do so, by leveraging online support conversations from Reddit. We evaluate the method across support skills, seekers' emotional intensity, and value reinforcement. Our method consistently outperforms various baselines, effectively exploring and eliciting values from seekers. Additionally, leveraging crowd knowledge from Reddit significantly enhances its effectiveness. Therapists highlighted its ability to validate seekers' challenges and emphasize positive aspects of their situationsunicodex2013both crucial elements of value reinforcement. Our work, being the first to integrate value reinforcement into emotional support systems, demonstrates its promise and establishes a foundation for future research.