5 citations · 9 across the 9 of their papers we have counts for
7 papers · 1 filter
Learning Task Skills and Goals Simultaneously from Physical Interaction
Haonan Chen, Ye-Ji Mun, Zhe Huang +4
In real-world human-robot systems, it is essential for a robot to comprehend human objectives and respond accordingly while performing an extended series of motor actions. Although…
Predicting Object Interactions with Behavior Primitives: An Application in Stowing Tasks
Haonan Chen, Yilong Niu, Kaiwen Hong +4
Stowing, the task of placing objects in cluttered shelves or bins, is a common task in warehouse and manufacturing operations. However, this task is still predominantly carried out…
Optimizing Factual Accuracy in Text Generation through Dynamic Knowledge Selection
Hongjin Qian, Zhicheng Dou, Jiejun Tan +6
Language models (LMs) have revolutionized the way we interact with information, but they often generate nonfactual text, raising concerns about their reliability. Previous methods…
PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systems
Aamir Hasan, Neeloy Chakraborty, Haonan Chen +3
Intelligent driving systems can be used to mitigate congestion through simple actions, thus improving many socioeconomic factors such as commute time and gas costs. However, these…
Towards Safe Multi-Level Human-Robot Interaction in Industrial Tasks
Zhe Huang, Ye-Ji Mun, Haonan Chen +7
Multiple levels of safety measures are required by multiple interaction modes which collaborative robots need to perform industrial tasks with human co-workers. We develop three in…
User-Friendly Safety Monitoring System for Manufacturing Cobots
Ye-Ji Mun, Zhe Huang, Haonan Chen +4
Collaborative robots are being increasingly utilized in industrial production lines due to their efficiency and accuracy. However, the close proximity between humans and robots can…
Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search
Kelong Mao, Zhicheng Dou, Fengran Mo +3
Precisely understanding users' contextual search intent has been an important challenge for conversational search. As conversational search sessions are much more diverse and long-…