6 papers
ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback
Jiacheng Ye, Jiahui Gao, Jiangtao Feng +3
Recently, dataset-generation-based zero-shot learning has shown promising results by training a task-specific model with a dataset synthesized from large pre-trained language model…
Heterogeneous Graph Neural Networks for Keyphrase Generation
Jiacheng Ye, Ruijian Cai, Tao Gui +1
The encoder-decoder framework achieves state-of-the-art results in keyphrase generation (KG) tasks by predicting both present keyphrases that appear in the source document and abse…
One2Set: Generating Diverse Keyphrases as a Set
Jiacheng Ye, Tao Gui, Yichao Luo +2
Recently, the sequence-to-sequence models have made remarkable progress on the task of keyphrase generation (KG) by concatenating multiple keyphrases in a predefined order as a tar…
Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning
Yichao Luo, Yige Xu, Jiacheng Ye +2
Aiming to generate a set of keyphrases, Keyphrase Generation (KG) is a classical task for capturing the central idea from a given document. Based on Seq2Seq models, the previous re…
Uncertainty-Aware Label Refinement for Sequence Labeling
Tao Gui, Jiacheng Ye, Qi Zhang +4
Conditional random fields (CRF) for label decoding has become ubiquitous in sequence labeling tasks. However, the local label dependencies and inefficient Viterbi decoding have alw…
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features
Tao Gui, Lizhi Qing, Qi Zhang +4
Multi-task learning (MTL) has received considerable attention, and numerous deep learning applications benefit from MTL with multiple objectives. However, constructing multiple rel…