# Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents

arXiv: https://arxiv.org/abs/2407.01824 · HTML: https://mlsanity.com/paper/2407.01824/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 65 references that are in the map.
- First posted on arXiv 1 Jul 2024.

## Builds on (most cited first, 4 of 4)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Large Language Models Produce Responses Perceived to be Empathic](https://mlsanity.com/paper/2403.18148/) (2024)
- [Platform for Situated Intelligence](https://mlsanity.com/paper/2103.15975/) (2021)
- [Ain't Misbehavin' -- Using LLMs to Generate Expressive Robot Behavior in Conversations with the Tabletop Robot Haru](https://mlsanity.com/paper/2402.11571/) (2024)

## Built on by (most cited first, 5 of 5)

- [Scaffolding Empathy: Training Counselors with Simulated Patients and Utterance-level Performance Visualizations](https://mlsanity.com/paper/2502.18673/) (2025)
- [Can LLMs Generate Behaviors for Embodied Virtual Agents Based on Personality Traits?](https://mlsanity.com/paper/2508.21087/) (2025)
- [Are You Listening to Me? Fine-Tuning Chatbots for Empathetic Dialogue](https://mlsanity.com/paper/2507.02537/) (2025)
- [SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses](https://mlsanity.com/paper/2607.02049/) (2026)
- [Does Listening Matter? Backchanneling and Nodding in AI Clone](https://mlsanity.com/paper/2608.19527/) (2026)

## Abstract (arXiv)

We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the speaker's affective state. Empathic grounding is generally required whenever the speaker's emotions are foregrounded and can make the grounding process more efficient and reliable by communicating both propositional and affective understanding. Both speaker expressions of affect and listener empathic grounding can be multimodal, including facial expressions and other nonverbal displays. Thus, models of empathic grounding for embodied agents should be multimodal to facilitate natural and efficient communication. We describe a multimodal model that takes as input user speech and facial expression to generate multimodal grounding moves for a listening agent using a large language model. We also describe a testbed to evaluate approaches to empathic grounding, in which a humanoid robot interviews a user about a past episode of pain and then has the user rate their perception of the robot's empathy. We compare our proposed model to one that only generates non-affective grounding cues in a between-subjects experiment. Findings demonstrate that empathic grounding increases user perceptions of empathy, understanding, emotional intelligence, and trust. Our work highlights the role of emotion awareness and multimodality in generating appropriate grounding moves for conversational agents.