Papers by Youxuan Jiang

3 papers
A Novel Workflow for Accurately and Efficiently Crowdsourcing Predicate Senses and Argument Labels (2020.findings-emnlp)

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Challenge: Prior attempts to develop crowdsourcing methods have either had low accuracy or required substantial expert annotation.
Approach: They propose a multi-stage crowd workflow that reduces expert involvement without sacrificing accuracy.
Outcome: The proposed method reduces expert effort by 4x, from 56% to 14% of cases.
Effective Crowdsourcing for a New Type of Summarization Task (N18-2)

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Challenge: Currently, summarization research focuses on summarizing the entire text, but in practice, readers are often interested in only one aspect of the document or conversation.
Approach: They propose a new task where the goal is to summarize a particular aspect of a document.
Outcome: The proposed task is based on a crowdsourced data collection workflow that allows users to collect high-quality summaries.
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases (D19-1)

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Challenge: CoSQL is a corpus for building cross-domain, general-purpose database querying dialogue systems.
Approach: They present a corpus for building cross-domain, general-purpose database querying dialogue systems . they use a Wizard-of-Oz collection of 3k turns plus 10k+ annotated SQL queries .
Outcome: The proposed corpus is based on a Wizard-of-Oz dataset of 3k dialogues querying 200 complex DBs spanning 138 domains.

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