26 citations · 29 across the 5 of their papers we have counts for
6 papers
Analyzing the Role of Semantic Representations in the Era of Large Language Models
Zhijing Jin, Yuen Chen, Fernando Gonzalez +5
Traditionally, natural language processing (NLP) models often use a rich set of features created by linguistic expertise, such as semantic representations. However, in the era of l…
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment
Zhijing Jin, Sydney Levine, Fernando Gonzalez +6
AI systems are becoming increasingly intertwined with human life. In order to effectively collaborate with humans and ensure safety, AI systems need to be able to understand, inter…
Differentially Private Language Models for Secure Data Sharing
Justus Mattern, Zhijing Jin, Benjamin Weggenmann +2
To protect the privacy of individuals whose data is being shared, it is of high importance to develop methods allowing researchers and companies to release textual data while provi…
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang
Daphna Keidar, Andreas Opedal, Zhijing Jin +1
Languages are continuously undergoing changes, and the mechanisms that underlie these changes are still a matter of debate. In this work, we approach language evolution through the…
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
Zhijing Jin, Julius von Kügelgen, Jingwei Ni +4
The principle of independent causal mechanisms (ICM) states that generative processes of real world data consist of independent modules which do not influence or inform each other.…
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning
Hongru Wang, Zhijing Jin, Jiarun Cao +2
Standard few-shot relation classification (RC) is designed to learn a robust classifier with only few labeled data for each class. However, previous works rarely investigate the ef…