# Coral: An Approach for Conversational Agents in Mental Health Applications

arXiv: https://arxiv.org/abs/2111.08545 · HTML: https://mlsanity.com/paper/2111.08545/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 6 references that are in the map.
- First posted on arXiv 16 Nov 2021.

## Builds on (most cited first, 3 of 3)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://mlsanity.com/paper/1911.00536/) (2019)
- [CAiRE: An Empathetic Neural Chatbot](https://mlsanity.com/paper/1907.12108/) (2019)

## Built on by (most cited first, 2 of 2)

- [Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactions](https://mlsanity.com/paper/2501.08393/) (2025)
- [Position: Beyond Assistance -- Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care](https://mlsanity.com/paper/2503.16456/) (2025)

## Abstract (arXiv)

It may be difficult for some individuals to open up and share their thoughts and feelings in front of a mental health expert. For those who are more at ease with a virtual agent, conversational agents can serve as an intermediate step in the right direction. The conversational agent must therefore be empathetic and able to conduct free-flowing conversations. To this effect, we present an approach for creating a generative empathetic open-domain chatbot that can be used for mental health applications. We leverage large scale pre-training and empathetic conversational data to make the responses more empathetic in nature and a multi-turn dialogue arrangement to maintain context. Our models achieve state-of-the-art results on the Empathetic Dialogues test set.