12 citations · 24 across the 7 of their papers we have counts for
7 papers
Synthetic Cross-language Information Retrieval Training Data
James Mayfield, Eugene Yang, Dawn Lawrie +5
A key stumbling block for neural cross-language information retrieval (CLIR) systems has been the paucity of training data. The appearance of the MS MARCO monolingual training set…
Impact of Subword Pooling Strategy on Cross-lingual Event Detection
Shantanu Agarwal, Steven Fincke, Chris Jenkins +2
Pre-trained multilingual language models (e.g., mBERT, XLM-RoBERTa) have significantly advanced the state-of-the-art for zero-shot cross-lingual information extraction. These langu…
Language Model Priming for Cross-Lingual Event Extraction
Steven Fincke, Shantanu Agarwal, Scott Miller +1
We present a novel, language-agnostic approach to "priming" language models for the task of event extraction, providing particularly effective performance in low-resource and zero-…
DEGREE: A Data-Efficient Generation-Based Event Extraction Model
I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee +4
Event extraction requires high-quality expert human annotations, which are usually expensive. Therefore, learning a data-efficient event extraction model that can be trained with o…
Use of Modality and Negation in Semantically-Informed Syntactic MT
Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr +5
This paper describes the resource- and system-building efforts of an eight-week Johns Hopkins University Human Language Technology Center of Excellence Summer Camp for Applied Lang…
Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach
Kathryn Baker, Michael Bloodgood, Chris Callison-Burch +5
We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic…