1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2024
Fewer Truncations Improve Language Modeling
Hantian Ding, Zijian Wang, Giovanni Paolini +4
In large language model training, input documents are typically concatenated together and then split into sequences of equal length to avoid padding tokens. Despite its efficiency,…
cs.CL2019★ 1 cited
SP-10K: A Large-scale Evaluation Set for Selectional Preference Acquisition
Hongming Zhang, Hantian Ding, Yangqiu Song
Selectional Preference (SP) is a commonly observed language phenomenon and proved to be useful in many natural language processing tasks. To provide a better evaluation method for…