Papers by Yuanliang Meng

3 papers
Automatic Labeling of Problem-Solving Dialogues for Computational Microgenetic Learning Analytics (L18-1)

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Challenge: This paper presents a recurrent neural network model to automate the analysis of students' computational thinking in problem-solving dialogue.
Approach: They propose a recurrent neural network model to automate the analysis of students' computational thinking in problem-solving dialogue.
Outcome: The proposed model outperforms the baseline model and outperformed the nave model by a large margin.
Triad-based Neural Network for Coreference Resolution (C18-1)

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Challenge: Entity coreference resolution aims to identify mentions that refer to the same entity.
Approach: They propose a triad-based neural network system that generates affinity scores between entity mentions for coreference resolution.
Outcome: The proposed system generates affinity scores between mentions for coreference resolution.
Context-Aware Neural Model for Temporal Information Extraction (P18-1)

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Challenge: Existing temporal information extraction systems rely on statistical learning with feature-engineered task-specific models.
Approach: They propose a context-aware neural network model for temporal information extraction using a global context layer.
Outcome: The proposed model outperforms existing models in terms of performance and performance . it is the first model to use NTM-like architecture to process the information from global context in discourse-scale natural text processing.

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