24 citations · 61 across the 9 of their papers we have counts for
11 papers
Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap Prediction
Ying-Ting Yeh, Janghoon Ock, Achuth Chandrasekhar +2
We investigate transformer-based language models, including RoBERTa, T5, Llama-3, and MatSciBERT, for predicting the band gaps of semiconductor materials directly from textual desc…
InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
Prakhar Gupta, Cathy Jiao, Yi-Ting Yeh +3
Instruction tuning is an emergent paradigm in NLP wherein natural language instructions are leveraged with language models to induce zero-shot performance on unseen tasks. Instruct…
Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges
Shikib Mehri, Jinho Choi, Luis Fernando D'Haro +13
This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog. The workshop explored the current state of the art along with its limitations and suggeste…
Are you doing what I say? On modalities alignment in ALFRED
Ting-Rui Chiang, Yi-Ting Yeh, Ta-Chung Chi +1
ALFRED is a recently proposed benchmark that requires a model to complete tasks in simulated house environments specified by instructions in natural language. We hypothesize that k…
Breaking Down Multilingual Machine Translation
Ting-Rui Chiang, Yi-Pei Chen, Yi-Ting Yeh +1
While multilingual training is now an essential ingredient in machine translation (MT) systems, recent work has demonstrated that it has different effects in different multilingual…
Improving Dialogue State Tracking by Joint Slot Modeling
Ting-Rui Chiang, Yi-Ting Yeh
Dialogue state tracking models play an important role in a task-oriented dialogue system. However, most of them model the slot types conditionally independently given the input. We…
A Comprehensive Assessment of Dialog Evaluation Metrics
Yi-Ting Yeh, Maxine Eskenazi, Shikib Mehri
Automatic evaluation metrics are a crucial component of dialog systems research. Standard language evaluation metrics are known to be ineffective for evaluating dialog. As such, re…
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…
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…
Natural Language Generation by Hierarchical Decoding with Linguistic Patterns
Shang-Yu Su, Kai-Ling Lo, Yi-Ting Yeh +1
Natural language generation (NLG) is a critical component in spoken dialogue systems. Classic NLG can be divided into two phases: (1) sentence planning: deciding on the overall sen…