PAR: Progress-Aligned Recurrence for Length Generalization in State Tracking

Pan Wang, Yihao Hu, Guangyuan Dong, Yitong Lin, Hang Wang, Zimi Liu, Zhihao Wen, Jianshe Li, Jiang-Ming Yang, Wei Wu, Yongqi Tong

Trains each loop of a language model to represent the state after one more operation, while keeping hidden-state norms stable. Combines this supervision with learned stopping and prefix self-distillation to test generalization to longer state-tracking problems without generating intermediate tokens.

First public: October 20, 2026 · Added to this list: October 22, 2026