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Found 8 papers, 4 papers with code
Multi-task Learning for Paraphrase Generation With Keyword and Part-of-Speech Reconstruction
The rationale is to capture simultaneously the possible keywords of a source sentence and the relations between them to facilitate the rewriting.
Survey of Natural Language Processing for Education: Taxonomy, Systematic Review, and Future Trends
Natural Language Processing (NLP) aims to analyze text or speech via techniques in the computer science field.
FlaCGEC: A Chinese Grammatical Error Correction Dataset with Fine-grained Linguistic Annotation
Chinese Grammatical Error Correction (CGEC) has been attracting growing attention from researchers recently.
CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure
To interpret these models, some probing methods have been applied.
GypSum: Learning Hybrid Representations for Code Summarization
Current deep learning models for code summarization generally follow the principle in neural machine translation and adopt the encoder-decoder framework, where the encoder learns the semantic representations from source code and the decoder transforms the learnt representations into human-readable text that describes the functionality of code snippets.
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model
More specifically, we construct a bipartite graph for programming problem embedding, and design an improved pre-training model PLCodeBERT for code embedding, as well as a double-sequence RNN model with exponential decay attention for effective feature fusion.
Deep Knowledge Tracing with Learning Curves
The model employs three-dimensional convolutional neural networks to explicitly learn a student's recent experience on applying the same knowledge concept with that in the next question, and fuses the learnt feature with the feature representing her overall latent knowledge state obtained using a classic LSTM network.
Discovering Traveling Companions using Autoencoders
The ability to discover moving objects that travel together, i. e., traveling companions, from their trajectories is desired by many applications such as intelligent transportation systems and location-based services.
