Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty. - Chao Xue; Yao Wang; Mengqiao Liu; Di Liang; Xingsheng Han; Peiyang Liu; Xianjie Wu; Chenyao Lu; Lei Jiang; Yu Lu; Haibo Shi; Shuang Liang; et al. (CoRR, 2026)

Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models. - Chao Xue; Yao Wang; Mengqiao Liu; Di Liang; Xingsheng Han; Peiyang Liu; Xianjie Wu; Chenyao Lu; Lei Jiang; Yu Lu; Haibo Shi; Shuang Liang; et al. (CoRR, 2026)

Parameter Importance is Not Static: Evolving Parameter Isolation for Supervised Fine-Tuning. - Zekai Lin; Chao Xue; Di Liang; Xingsheng Han; Peiyang Liu; Xianjie Wu; Lei Jiang; Yu Lu; Haibo Shi; Shuang Liang; Minlong Peng (CoRR, 2026)