# EthicMind: A Risk-Aware Framework for Ethical-Emotional Alignment in Multi-Turn Dialogue

Source: [EthicMind: A Risk-Aware Framework for Ethical-Emotional Alignment in Multi-Turn Dialogue](<https://www.sota2.com/research/paper/69dc78727d0172140ec78a10>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-04-14T05:00:04.234Z

Authors: Jiawen Deng, Wei Li, Wentao Zhang, Ziyun Jiao, Fuji Ren

Published: 2026-04-10T12:28:32.000Z

## Abstract

Intelligent dialogue systems are increasingly deployed in emotionally and ethically sensitive settings, where failures in either emotional attunement or ethical judgment can cause significant harm. Existing dialogue models typically address empathy and ethical safety in isolation, and often fail to adapt their behavior as ethical risk and user emotion evolve across multi-turn interactions. We formulate ethical-emotional alignment in dialogue as an explicit turn-level decision problem, and propose \\textsc{EthicMind}, a risk-aware framework that implements this formulation in multi-turn dialogue at inference time. At each turn, \\textsc{EthicMind} jointly analyzes ethical risk signals and user emotion, plans a high-level response strategy, and generates context-sensitive replies that balance ethical guidance with emotional engagement, without requiring additional model training. To evaluate alignment behavior under ethically complex interactions, we introduce a risk-stratified, multi-turn evaluation protocol with a context-aware user simulation procedure. Experimental results show that \\textsc{EthicMind} achieves more consistent ethical guidance and emotional engagement than competitive baselines, particularly in high-risk and morally ambiguous scenarios.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Dialogue Generation on Dialogue-level evaluation Ethical and Affective Alignment](<https://www.sota2.com/research/sota/dialogue-generation-on-dialogue-level-evaluation-ethical-and-affective-alignment.md>): Dialogue Generation; Dialogue-level evaluation Ethical and Affective Alignment; Respectful Tone: 8.1739.

- [Ethical and Affective Alignment on Risk-stratified dataset](<https://www.sota2.com/research/sota/ethical-and-affective-alignment-on-risk-stratified-dataset.md>): Ethical and Affective Alignment; Risk-stratified dataset; Respectful Tone: 8.5787.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2604.09265>)

[PDF](<https://arxiv.org/pdf/2604.09265.pdf>)