3 papers
cs.CL2026
Modeling the Arrival Time of Information-Bearing Events in Natural Language
Leyi Lao, Yulin Ou, Yang Xu +1
Understanding how information is distributed over time is fundamental to modeling natural language. While existing empirical studies primarily rely on post-hoc analysis of informat…
cs.LG2026
Fast and Accurate Probing of In-Training LLMs' Downstream Performances
Zhichen Liu, Tianle Lun, Zhibin Wen +7
The paradigm of scaling Large Language Models (LLMs) in both parameter size and test time has pushed the boundaries of AI capabilities, but at the cost of making the traditional ge…
cs.CL2025
Identifying the Periodicity of Information in Natural Language
Yulin Ou, Yu Wang, Yang Xu +1
Recent theoretical advancement of information density in natural language has brought the following question on desk: To what degree does natural language exhibit periodicity patte…