3 citations · 5 across the 4 of their papers we have counts for
4 papers
Automating Intervention Discovery from Scientific Literature: A Progressive Ontology Prompting and Dual-LLM Framework
Yuting Hu, Dancheng Liu, Qingyun Wang +5
Identifying effective interventions from the scientific literature is challenging due to the high volume of publications, specialized terminology, and inconsistent reporting format…
Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
Chi Han, Qizheng He, Charles Yu +3
Probabilistic logical rule learning has shown great strength in logical rule mining and knowledge graph completion. It learns logical rules to predict missing edges by reasoning on…
ADEPT: A DEbiasing PrompT Framework
Ke Yang, Charles Yu, Yi Fung +2
Several works have proven that finetuning is an applicable approach for debiasing contextualized word embeddings. Similarly, discrete prompts with semantic meanings have shown to b…
Word Frequency Does Not Predict Grammatical Knowledge in Language Models
Charles Yu, Ryan Sie, Nico Tedeschi +1
Neural language models learn, to varying degrees of accuracy, the grammatical properties of natural languages. In this work, we investigate whether there are systematic sources of…