73 citations · 108 across the 9 of their papers we have counts for
13 papers
Graph Learning for Cognitive Digital Twins in Manufacturing Systems
Trier Mortlock, Deepan Muthirayan, Shih-Yuan Yu +2
Future manufacturing requires complex systems that connect simulation platforms and virtualization with physical data from industrial processes. Digital twins incorporate a physica…
HW2VEC: A Graph Learning Tool for Automating Hardware Security
Shih-Yuan Yu, Rozhin Yasaei, Qingrong Zhou +2
The time-to-market pressure and continuous growing complexity of hardware designs have promoted the globalization of the Integrated Circuit (IC) supply chain. However, such globali…
Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning
Haoran Wang, Shi Yu
Machine Learning (ML) has been embraced as a powerful tool by the financial industry, with notable applications spreading in various domains including investment management. In thi…
Few-Shot Conversational Dense Retrieval
Shi Yu, Zhenghao Liu, Chenyan Xiong +2
Dense retrieval (DR) has the potential to resolve the query understanding challenge in conversational search by matching in the learned embedding space. However, this adaptation is…
Exploring Fluent Query Reformulations with Text-to-Text Transformers and Reinforcement Learning
Jerry Zikun Chen, Shi Yu, Haoran Wang
Query reformulation aims to alter noisy or ambiguous text sequences into coherent ones closer to natural language questions. This is to prevent errors from propagating in a client-…
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search
Chenyan Xiong, Zhenghao Liu, Si Sun +7
Neural rankers based on deep pretrained language models (LMs) have been shown to improve many information retrieval benchmarks. However, these methods are affected by their the cor…