6 citations · 12 across the 3 of their papers we have counts for
6 papers · 1 filter
SNaRe: Domain-aware Data Generation for Low-Resource Event Detection
Tanmay Parekh, Yuxuan Dong, Lucas Bandarkar +4
Event Detection (ED) -- the task of identifying event mentions from natural language text -- is critical for enabling reasoning in highly specialized domains such as biomedicine, l…
Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction
Kuan-Hao Huang, I-Hung Hsu, Premkumar Natarajan +2
We present a study on leveraging multilingual pre-trained generative language models for zero-shot cross-lingual event argument extraction (EAE). By formulating EAE as a language g…
ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoning
Rujun Han, I-Hung Hsu, Jiao Sun +4
Understanding how events are semantically related to each other is the essence of reading comprehension. Recent event-centric reading comprehension datasets focus mostly on event a…
Deep Structured Neural Network for Event Temporal Relation Extraction
Rujun Han, I-Hung Hsu, Mu Yang +3
We propose a novel deep structured learning framework for event temporal relation extraction. The model consists of 1) a recurrent neural network (RNN) to learn scoring functions f…
NIESR: Nuisance Invariant End-to-end Speech Recognition
I-Hung Hsu, Ayush Jaiswal, Premkumar Natarajan
Deep neural network models for speech recognition have achieved great success recently, but they can learn incorrect associations between the target and nuisance factors of speech…
Mitigating the Impact of Speech Recognition Errors on Chatbot using Sequence-to-Sequence Model
Pin-Jung Chen, I-Hung Hsu, Yi-Yao Huang +1
We apply sequence-to-sequence model to mitigate the impact of speech recognition errors on open domain end-to-end dialog generation. We cast the task as a domain adaptation problem…