HyCoRA: Hyper-Contrastive Role-Adaptive Learning for Role-Playing

Shihao Yang; Zhicong Lu; Yong Yang; Bo Lv; Yang Shen; Nayu Liu

AAAI 2026technical0 citations

HyCoRA: Hyper-Contrastive Role-Adaptive Learning for Role-Playing

Shihao Yang, Zhicong Lu, Yong Yang, Bo Lv, Yang Shen, Nayu Liu

Abstract

Multi-character role-playing aims to equip models with the capability to simulate diverse roles. Existing methods either use one shared parameterized module across all roles or assign a separate parameterized module to each role. However, the role-shared module may ignore distinct traits of each role, weakening personality learning, while the role-specific module may overlook shared traits across multiple roles, hindering commonality modeling. In this paper, we propose a novel HyCoRA: Hyper-Contrastive Role-Adaptive learning framework, which efficiently improves multi-character role-playing agents

BibTeX

@inproceedings{aaai2026_hycorahypercontr,
  title = {HyCoRA: Hyper-Contrastive Role-Adaptive Learning for Role-Playing},
  author = {Shihao Yang and Zhicong Lu and Yong Yang and Bo Lv and Yang Shen and Nayu Liu},
  booktitle = {AAAI 2026},
  year = {2026}
}