80 citations · 380 across the 52 of their papers we have counts for
7 papers · 1 filter
Entity Set Co-Expansion in StackOverflow
Yu Zhang, Yunyi Zhang, Yucheng Jiang +5
Given a few seed entities of a certain type (e.g., Software or Programming Language), entity set expansion aims to discover an extensive set of entities that share the same type as…
Tuning Language Models as Training Data Generators for Augmentation-Enhanced Few-Shot Learning
Yu Meng, Martin Michalski, Jiaxin Huang +3
Recent studies have revealed the intriguing few-shot learning ability of pretrained language models (PLMs): They can quickly adapt to a new task when fine-tuned on a small amount o…
Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
Bowen Jin, Yu Zhang, Qi Zhu +1
Representation learning on networks aims to derive a meaningful vector representation for each node, thereby facilitating downstream tasks such as link prediction, node classificat…
Seed-Guided Topic Discovery with Out-of-Vocabulary Seeds
Yu Zhang, Yu Meng, Xuan Wang +2
Discovering latent topics from text corpora has been studied for decades. Many existing topic models adopt a fully unsupervised setting, and their discovered topics may not cater t…
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification
Yu Zhang, Zhihong Shen, Chieh-Han Wu +5
Large-scale multi-label text classification (LMTC) aims to associate a document with its relevant labels from a large candidate set. Most existing LMTC approaches rely on massive h…
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
Yu Meng, Yunyi Zhang, Jiaxin Huang +2
Topic models have been the prominent tools for automatic topic discovery from text corpora. Despite their effectiveness, topic models suffer from several limitations including the…
Generating Training Data with Language Models: Towards Zero-Shot Language Understanding
Yu Meng, Jiaxin Huang, Yu Zhang +1
Pretrained language models (PLMs) have demonstrated remarkable performance in various natural language processing tasks: Unidirectional PLMs (e.g., GPT) are well known for their su…