138 citations · 480 across the 46 of their papers we have counts for
14 papers · 2 filters
Tree Transformer: Integrating Tree Structures into Self-Attention
Yau-Shian Wang, Hung-Yi Lee, Yun-Nung Chen
Pre-training Transformer from large-scale raw texts and fine-tuning on the desired task have achieved state-of-the-art results on diverse NLP tasks. However, it is unclear what the…
Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation
Alexander Te-Wei Shieh, Yung-Sung Chuang, Shang-Yu Su +1
Randomized controlled trials (RCTs) represent the paramount evidence of clinical medicine. Using machines to interpret the massive amount of RCTs has the potential of aiding clinic…
DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs
Yi-Lin Tuan, Yun-Nung Chen, Hung-yi Lee
Data-driven, knowledge-grounded neural conversation models are capable of generating more informative responses. However, these models have not yet demonstrated that they can zero-…
Learning ASR-Robust Contextualized Embeddings for Spoken Language Understanding
Chao-Wei Huang, Yun-Nung Chen
Employing pre-trained language models (LM) to extract contextualized word representations has achieved state-of-the-art performance on various NLP tasks. However, applying this tec…
An Empirical Study of Content Understanding in Conversational Question Answering
Ting-Rui Chiang, Hao-Tong Ye, Yun-Nung Chen
With a lot of work about context-free question answering systems, there is an emerging trend of conversational question answering models in the natural language processing field. T…
QAInfomax: Learning Robust Question Answering System by Mutual Information Maximization
Yi-Ting Yeh, Yun-Nung Chen
Standard accuracy metrics indicate that modern reading comprehension systems have achieved strong performance in many question answering datasets. However, the extent these systems…
Entropy-Enhanced Multimodal Attention Model for Scene-Aware Dialogue Generation
Kuan-Yen Lin, Chao-Chun Hsu, Yun-Nung Chen +1
With increasing information from social media, there are more and more videos available. Therefore, the ability to reason on a video is important and deserves to be discussed. TheD…
Reactive Multi-Stage Feature Fusion for Multimodal Dialogue Modeling
Yi-Ting Yeh, Tzu-Chuan Lin, Hsiao-Hua Cheng +3
Visual question answering and visual dialogue tasks have been increasingly studied in the multimodal field towards more practical real-world scenarios. A more challenging task, aud…
FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension
Yi-Ting Yeh, Yun-Nung Chen
Conversational machine comprehension requires deep understanding of the dialogue flow, and the prior work proposed FlowQA to implicitly model the context representations in reasoni…
Dual Supervised Learning for Natural Language Understanding and Generation
Shang-Yu Su, Chao-Wei Huang, Yun-Nung Chen
Natural language understanding (NLU) and natural language generation (NLG) are both critical research topics in the NLP field. Natural language understanding is to extract the core…
Mitigating the Impact of Speech Recognition Errors on Spoken Question Answering by Adversarial Domain Adaptation
Chia-Hsuan Lee, Yun-Nung Chen, Hung-Yi Lee
Spoken question answering (SQA) is challenging due to complex reasoning on top of the spoken documents. The recent studies have also shown the catastrophic impact of automatic spee…
Knowledge-Grounded Response Generation with Deep Attentional Latent-Variable Model
Hao-Tong Ye, Kai-Ling Lo, Shang-Yu Su +1
End-to-end dialogue generation has achieved promising results without using handcrafted features and attributes specific for each task and corpus. However, one of the fatal drawbac…
Learning Multi-Level Information for Dialogue Response Selection by Highway Recurrent Transformer
Ting-Rui Chiang, Chao-Wei Huang, Shang-Yu Su +1
With the increasing research interest in dialogue response generation, there is an emerging branch formulating this task as selecting next sentences, where given the partial dialog…
RAP-Net: Recurrent Attention Pooling Networks for Dialogue Response Selection
Chao-Wei Huang, Ting-Rui Chiang, Shang-Yu Su +1
The response selection has been an emerging research topic due to the growing interest in dialogue modeling, where the goal of the task is to select an appropriate response for con…