5 citations · 15 across the 12 of their papers we have counts for
4 papers · 2 filters
CLIP also Understands Text: Prompting CLIP for Phrase Understanding
An Yan, Jiacheng Li, Wanrong Zhu +3
Contrastive Language-Image Pretraining (CLIP) efficiently learns visual concepts by pre-training with natural language supervision. CLIP and its visual encoder have been explored o…
SPOT: Knowledge-Enhanced Language Representations for Information Extraction
Jiacheng Li, Yannis Katsis, Tyler Baldwin +4
Knowledge-enhanced pre-trained models for language representation have been shown to be more effective in knowledge base construction tasks (i.e.,~relation extraction) than languag…
Fine-grained Contrastive Learning for Relation Extraction
William Hogan, Jiacheng Li, Jingbo Shang
Recent relation extraction (RE) works have shown encouraging improvements by conducting contrastive learning on silver labels generated by distant supervision before fine-tuning on…
UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining
Jiacheng Li, Jingbo Shang, Julian McAuley
High-quality phrase representations are essential to finding topics and related terms in documents (a.k.a. topic mining). Existing phrase representation learning methods either sim…