StageWell: A Process-Aligned Chinese Corpus for Positive-Psychology Support Dialogue

2026-08-29

AI Summary

本文通过构建StageWell语料库和HQS协议，解决了积极心理学对话中缺乏过程监督的问题，提高了模型在多轮支持过程中的控制力、响应质量和安全性。

Abstract

Positive psychology dialogue aims to support emotional distress and positive resource building, requiring models to produce not only empathetic replies but also coherent progression through a multi-turn support process. Existing resources often reduce supervision to turn-level strategies or holistic preference labels, leaving process position, support function, and local repair targets implicit. We introduce StageWell, a process-aligned Chinese corpus for positive psychology dialogue, together with HQS, a structured protocol for data construction and evaluation. StageWell organizes support into a six-stage support process and uses a multi-agent whole-dialogue rewriting workflow to construct 12,445 SFT instances, 1,849 DPO preference pairs, and a GroundTruth subset of 120 expert-revised dialogues and 977 QA pairs. Guided by HQS, DPO pairs are built as process-localized repairs: flawed model outputs are used as rejected responses, and targeted rewrites under the same context and stage constraint are used as chosen responses. Across four 9B-14B open-source LLMs, this supervision yields robust gains in process control, response quality, and safety. Averaged across models, BERTScore improves by 0.037, Q-Overall increases by 1.32 points, S-exact increases by 0.236, and the H-critical rate decreases by 0.167. These results highlight the value of modeling supportive dialogue as a structured multi-turn support process rather than as single-turn response generation.

Problem

• positive psychology dialogue
• process-aligned
• multi-turn support process

Innovation

• StageWell
• HQS
• multi-turn support process
• process-localized repairs
• whole-dialogue rewriting