4 citations · 8 across the 4 of their papers we have counts for
4 papers
Step by Step to Fairness: Attributing Societal Bias in Task-oriented Dialogue Systems
Hsuan Su, Rebecca Qian, Chinnadhurai Sankar +4
Recent works have shown considerable improvements in task-oriented dialogue (TOD) systems by utilizing pretrained large language models (LLMs) in an end-to-end manner. However, the…
Perturbation Augmentation for Fairer NLP
Rebecca Qian, Candace Ross, Jude Fernandes +3
Unwanted and often harmful social biases are becoming ever more salient in NLP research, affecting both models and datasets. In this work, we ask whether training on demographicall…
Many Episode Learning in a Modular Embodied Agent via End-to-End Interaction
Yuxuan Sun, Ethan Carlson, Rebecca Qian +2
In this work we give a case study of an embodied machine-learning (ML) powered agent that improves itself via interactions with crowd-workers. The agent consists of a set of module…
Human Evaluation of Conversations is an Open Problem: comparing the sensitivity of various methods for evaluating dialogue agents
Eric Michael Smith, Orion Hsu, Rebecca Qian +3
At the heart of improving conversational AI is the open problem of how to evaluate conversations. Issues with automatic metrics are well known (Liu et al., 2016, arXiv:1603.08023),…