Luheng He

5 paper cards in Mova's library · 2015–2018

Luheng He wrote 5 of the papers Mova reads, in 2015–2018, most of them on Semantic role labeling, Coreference resolution; often with Luke Zettlemoyer, Mike Lewis, Julian Michael.

The profile is the library's match of the name; two people with one name are not always told apart.

Papers

Large-Scale QA-SRL Parsing (2018)
The paper releases QA-SRL Bank 2.0, which has 265,140 valid question-answer pairs for 64,018 sentences and 133,479 verbs across Wikipedia, Wikinews and science textbooks.
Crowdsourcing Question-Answer Meaning Representations (2018)
A QAMR represents a sentence's predicate-argument structure as a set of free-form wh-question / answer-span pairs about all its content words, not only verbs («How old is Pierre Vinken? – 61 years old», «What will he join the board as? – nonexecutive director»).
End-to-end Neural Coreference Resolution (2017)
The first coreference model trained end to end without a parser or a mention detector. Every span up to 10 words is a candidate; each span gets a mention score and each pair an antecedent score, and a span chooses among all earlier spans plus a dummy antecedent fixed at score 0 (no link, or not a mention). Span…
Deep Semantic Role Labeling: What Works and What's Next (2017)
A neural SRL model that treats each predicate's arguments as BIO tags over the sentence, with no syntax input.
Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language (2015)
The paper introduces question-answer driven semantic role labeling (QA-SRL): each verbal predicate is labeled with wh-questions, such as "Who finished something?", and each question is answered by phrases of the sentence.