4 citations · 7 across the 4 of their papers we have counts for
4 papers
Revealing the Learning Dynamics of Long-Context Continual Pre-training
Yupu Liang, Shuang Chen, Guanwei Zhang +2
Existing studies on Long-Context Continual Pre-training (LCCP) mainly focus on small-scale models and limited data regimes (tens of billions of tokens). We argue that directly migr…
CL-bench: A Benchmark for Context Learning
Shihan Dou, Ming Zhang, Zhangyue Yin +24
Current language models (LMs) excel at reasoning over prompts using pre-trained knowledge. However, real-world tasks are far more complex and context-dependent: models must learn f…
Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency Detection
Shaolei Wang, Zhongyuan Wang, Wanxiang Che +1
Most existing approaches to disfluency detection heavily rely on human-annotated corpora, which is expensive to obtain in practice. There have been several proposals to alleviate t…
Multi-Task Self-Supervised Learning for Disfluency Detection
Shaolei Wang, Wanxiang Che, Qi Liu +3
Most existing approaches to disfluency detection heavily rely on human-annotated data, which is expensive to obtain in practice. To tackle the training data bottleneck, we investig…