The success of bidirectional encoders using masked language models, such as BERT, on
numerous natural language processing tasks has prompted researchers to attempt to …

Large pre-trained language models (LMs) have demonstrated the ability to obtain good
performance on downstream tasks with limited examples in cross-lingual settings. However …

In this paper, we address the Event Detection task under a zero-shot cross-lingual setting
where a model is trained on a source language but evaluated on a distinct target language …

Translating training data into many languages has emerged as a practical solution for
improving cross-lingual transfer. For tasks that involve span-level annotations, such as …

Claim span identification (CSI) is an important step in fact-checking pipelines, aiming to
identify text segments that contain a checkworthy claim or assertion in a social media post …

In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage
retrieval. DuReader_retrieval contains more than 90K queries and over 8M unique …

Natural language tasks like Named Entity Recognition (NER) in the clinical domain on non-
English texts can be very time-consuming and expensive due to the lack of annotated data …

We present a novel iterative extraction model, IterX, for extracting complex relations, or
templates (ie, N-tuples representing a mapping from named slots to spans of text) within a …

Translating training data into target languages has proven beneficial for cross-lingual
transfer. However, for structure extraction tasks, translating data requires a label projection …

Relation extraction (RE) is a fundamental task in information extraction, whose extension to
multilingual settings has been hindered by the lack of supervised resources comparable in …