64 citations · 107 across the 6 of their papers we have counts for
12 papers
One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval
Akari Asai, Xinyan Yu, Jungo Kasai +1
We present Cross-lingual Open-Retrieval Answer Generation (CORA), the first unified many-to-many question answering (QA) model that can answer questions across many languages, even…
Probing Across Time: What Does RoBERTa Know and When?
Leo Z. Liu, Yizhong Wang, Jungo Kasai +2
Models of language trained on very large corpora have been demonstrated useful for NLP. As fixed artifacts, they have become the object of intense study, with many researchers "pro…
Finetuning Pretrained Transformers into RNNs
Jungo Kasai, Hao Peng, Yizhe Zhang +6
Transformers have outperformed recurrent neural networks (RNNs) in natural language generation. But this comes with a significant computational cost, as the attention mechanism's c…
XOR QA: Cross-lingual Open-Retrieval Question Answering
Akari Asai, Jungo Kasai, Jonathan H. Clark +3
Multilingual question answering tasks typically assume answers exist in the same language as the question. Yet in practice, many languages face both information scarcity -- where l…
Non-Autoregressive Machine Translation with Disentangled Context Transformer
Jungo Kasai, James Cross, Marjan Ghazvininejad +1
State-of-the-art neural machine translation models generate a translation from left to right and every step is conditioned on the previously generated tokens. The sequential nature…
Cracking the Contextual Commonsense Code: Understanding Commonsense Reasoning Aptitude of Deep Contextual Representations
Jeff Da, Jungo Kasai
Pretrained deep contextual representations have advanced the state-of-the-art on various commonsense NLP tasks, but we lack a concrete understanding of the capability of these mode…