2 citations · 4 across the 8 of their papers we have counts for
8 papers
Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results
Philipp Ennen, Po-Chun Hsu, Chan-Jan Hsu +6
In this paper we present the multilingual language model BLOOM-zh that features enhanced support for Traditional Chinese. BLOOM-zh has its origins in the open-source BLOOM models p…
Roof-Transformer: Divided and Joined Understanding with Knowledge Enhancement
Wei-Lin Liao, Cheng-En Su, Wei-Yun Ma
Recent work on enhancing BERT-based language representation models with knowledge graphs (KGs) and knowledge bases (KBs) has yielded promising results on multiple NLP tasks. State-…
DCT: Dynamic Compressive Transformer for Modeling Unbounded Sequence
Kai-Po Chang, Wei-Yun Ma
In this paper, we propose Dynamic Compressive Transformer (DCT), a transformer-based framework for modeling the unbounded sequence. In contrast to the previous baselines which appe…
H-FND: Hierarchical False-Negative Denoising for Distant Supervision Relation Extraction
Jhih-Wei Chen, Tsu-Jui Fu, Chen-Kang Lee +1
Although distant supervision automatically generates training data for relation extraction, it also introduces false-positive (FP) and false-negative (FN) training instances to the…
Predict and Use Latent Patterns for Short-Text Conversation
Hung-Ting Chen, Yu-Chieh Chao, Ta-Hsuan Chao +1
Many neural network models nowadays have achieved promising performances in Chit-chat settings. The majority of them rely on an encoder for understanding the post and a decoder for…
Why Attention? Analyzing and Remedying BiLSTM Deficiency in Modeling Cross-Context for NER
Peng-Hsuan Li, Tsu-Jui Fu, Wei-Yun Ma
State-of-the-art approaches of NER have used sequence-labeling BiLSTM as a core module. This paper formally shows the limitation of BiLSTM in modeling cross-context patterns. Two t…
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER
Peng-Hsuan Li, Tsu-Jui Fu, Wei-Yun Ma
BiLSTM has been prevalently used as a core module for NER in a sequence-labeling setup. State-of-the-art approaches use BiLSTM with additional resources such as gazetteers, languag…
CA-EHN: Commonsense Analogy from E-HowNet
Peng-Hsuan Li, Tsan-Yu Yang, Wei-Yun Ma
Embedding commonsense knowledge is crucial for end-to-end models to generalize inference beyond training corpora. However, existing word analogy datasets have tended to be handcraf…