Papers with end-to-end neural network model

2 papers
Recovering dropped pronouns in Chinese conversations via modeling their referents (N19-1)

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Challenge: Pronouns are often dropped in conversational genres as their referents can be easily understood from context.
Approach: They propose an end-to-end neural network model to recover dropped pronouns in conversational data.
Outcome: The proposed model improves on three different conversational genres.
Movie Plot Analysis via Turning Point Identification (D19-1)

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Challenge: Using computational literary analysis, we analyze novels, plays, and screenplays for their turning points.
Approach: They propose to use turning points to analyze screenplays and plot synopses as tools for analysis . they propose to build a neural network model that identifies turning points in plot synoopse .
Outcome: The proposed model outperforms baselines based on state-of-the-art sentence representations and expected position of turning points.

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