BEYOND DIALOGUE: A Profile-Dialogue Alignment Framework Towards General Role-Playing Language Model
Yeyong Yu, Runsheng Yu, Haojie Wei, Zhanqiu Zhang, Quan Qian

TL;DR
This paper introduces BEYOND DIALOGUE, a framework that improves role-playing language models by aligning dialogue with profile traits at the sentence level, reducing biases and enhancing role adherence.
Contribution
The framework employs 'beyond dialogue' tasks and innovative prompting to achieve fine-grained profile-dialogue alignment, fully automated and low-cost.
Findings
Outperforms existing role-playing models in profile adherence
Effectively reduces training biases and conflicts
Achieves fine-grained sentence-level alignment
Abstract
The rapid advancement of large language models (LLMs) has revolutionized role-playing, enabling the development of general role-playing models. However, current role-playing training has two significant issues: (I) Using a predefined role profile to prompt dialogue training for specific scenarios usually leads to inconsistencies and even conflicts between the dialogue and the profile, resulting in training biases. (II) The model learns to imitate the role based solely on the profile, neglecting profile-dialogue alignment at the sentence level. In this work, we propose a simple yet effective framework called BEYOND DIALOGUE, designed to overcome these hurdles. This framework innovatively introduces "beyond dialogue" tasks to align dialogue with profile traits based on each specific scenario, thereby eliminating biases during training. Furthermore, by adopting an innovative prompting…
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Taxonomy
TopicsSpeech and dialogue systems · Topic Modeling · Natural Language Processing Techniques
MethodsALIGN
