# When and How to Express Empathy in Human-Robot Interaction Scenarios

arXiv: https://arxiv.org/abs/2509.25200 · HTML: https://mlsanity.com/paper/2509.25200/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2025.

## Built on by (most cited first, 4 of 4)

- [A Lightweight Transformer for Pain Recognition from Brain Activity](https://mlsanity.com/paper/2604.16491/) (2026)
- [One-Block Transformer (1BT) for EEG-Based Cognitive Workload Assessment](https://mlsanity.com/paper/2605.00856/) (2026)
- [Efficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks](https://mlsanity.com/paper/2607.20820/) (2026)
- [Multimodal Voice Activity Projection for Turn-Taking in Social Robots with Voice-Activity-Related Pretrained Encoders](https://mlsanity.com/paper/2607.07294/) (2026)

## Abstract (arXiv)

Incorporating empathetic behavior into robots can improve their social effectiveness and interaction quality. In this paper, we present whEE (when and how to express empathy), a framework that enables social robots to detect when empathy is needed and generate appropriate responses. Using large language models, whEE identifies key behavioral empathy cues in human interactions. We evaluate it in human-robot interaction scenarios with our social robot, Haru. Results show that whEE effectively identifies and responds to empathy cues, providing valuable insights for designing social robots capable of adaptively modulating their empathy levels across various interaction contexts.