Zitao Liu
7 papers in the PaperMetrix corpus
Papers by this author
-
Upgrading CRFS to JRFS and its Benefits to Sequence Modeling and Labeling
2020
Two important sequence tasks are sequence modeling and labeling. Sequence modeling involves determining the probabilities of sequences, e.g. language modeling. It is still difficult to improve language modeling with additional relevant tags, e.g. part-of-speech (POS) …
-
Recent Advances in Multimodal Educational Data Mining in K-12 Education
2020
Recently we have seen a rapid rise in the amount of education data available through the digitization of education. This huge amount of education data usually exhibits in a mixture form of images, videos, speech, …
-
Node Similarity Preserving Graph Convolutional Networks
2020 · arXiv (Cornell University)
Graph Neural Networks (GNNs) have achieved tremendous success in various real-world applications due to their strong ability in graph representation learning. GNNs explore the graph structure and node features by aggregating and transforming information within …
-
Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
2021 · arXiv (Cornell University)
Generating long and coherent text is an important but challenging task, particularly for open-ended language generation tasks such as story generation. Despite the success in modeling intra-sentence coherence, existing generation models (e.g., BART) still struggle …
-
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations
2021 · arXiv (Cornell University)
Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms. However, these models are facing challenges of overfitting with limited labels and low model generalization abilities. In this paper, we present a Cross-modal Transformer …
-
DialogID: A Dialogic Instruction Dataset for Improving Teaching Effectiveness in Online Environments
2022 · arXiv (Cornell University)
Online dialogic instructions are a set of pedagogical instructions used in real-world online educational contexts to motivate students, help understand learning materials, and build effective study habits. In spite of the popularity and advantages of …
-
Enhancing Deep Knowledge Tracing with Auxiliary Tasks
2023
Knowledge tracing (KT) is the problem of predicting students’ future performance based on their historical interactions with intelligent tutoring systems. Recent studies have applied multiple types of deep neural networks to solve the KT problem. …