6 papers
CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment
Radin Shayanfar, Chu Fei Luo, Rohan Bhambhoria +2
Building Task-Oriented Dialogue (TOD) systems that generalize across different tasks remains a challenging problem. Data-driven approaches often struggle to transfer effectively to…
Towards Low-Resource Alignment to Diverse Perspectives with Sparse Feedback
Chu Fei Luo, Samuel Dahan, Xiaodan Zhu
As language models have a greater impact on society, it is important to ensure they are aligned to a diverse range of perspectives and are able to reflect nuance in human values. H…
MedCritical: Enhancing Medical Reasoning in Small Language Models via Self-Collaborative Correction
Xinchun Su, Chunxu Luo, Yixuan Li +2
In the field of medicine, complex reasoning tasks such as clinical diagnosis, treatment planning, and medical knowledge integration pose significant challenges, where small languag…
Qianfan-VL: Domain-Enhanced Universal Vision-Language Models
Daxiang Dong, Mingming Zheng, Dong Xu +32
We present Qianfan-VL, a series of multimodal large language models ranging from 3B to 70B parameters, achieving state-of-the-art performance through innovative domain enhancement…
Red-Teaming for Inducing Societal Bias in Large Language Models
Chu Fei Luo, Ahmad Ghawanmeh, Bharat Bhimshetty +4
Ensuring the safe deployment of AI systems is critical in industry settings where biased outputs can lead to significant operational, reputational, and regulatory risks. Thorough e…
Misinformation with Legal Consequences (MisLC): A New Task Towards Harnessing Societal Harm of Misinformation
Chu Fei Luo, Radin Shayanfar, Rohan Bhambhoria +2
Misinformation, defined as false or inaccurate information, can result in significant societal harm when it is spread with malicious or even innocuous intent. The rapid online info…