27 citations · 66 across the 12 of their papers we have counts for
12 papers
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…
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…
Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers
Linyuan Gong, Chenyan Xiong, Xiaodong Liu +5
This paper explores the effectiveness of model-generated signals in improving zero-shot generalization of text-to-text Transformers such as T5. We study various designs to pretrain…
Unsupervised Dense Retrieval Training with Web Anchors
Yiqing Xie, Xiao Liu, Chenyan Xiong
In this work, we present an unsupervised retrieval method with contrastive learning on web anchors. The anchor text describes the content that is referenced from the linked page. T…
Open-Vocabulary Argument Role Prediction for Event Extraction
Yizhu Jiao, Sha Li, Yiqing Xie +3
The argument role in event extraction refers to the relation between an event and an argument participating in it. Despite the great progress in event extraction, existing studies…
Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration
Zhe Huang, Ye-Ji Mun, Xiang Li +6
A robot needs multiple interaction modes to robustly collaborate with a human in complicated industrial tasks. We develop a Coexistence-and-Cooperation (CoCo) human-robot collabora…
Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks
Zhe Huang, Ye-Ji Mun, Xiang Li +6
Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intentio…
P4E: Few-Shot Event Detection as Prompt-Guided Identification and Localization
Sha Li, Liyuan Liu, Yiqing Xie +2
We propose P4E, an identify-and-localize event detection framework that integrates the best of few-shot prompting and structured prediction. Our framework decomposes event detectio…
Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion
Yiqing Xie, Jiaming Shen, Sha Li +2
Document-level relation extraction (DocRE) aims to extract semantic relations among entity pairs in a document. Typical DocRE methods blindly take the full document as input, while…
CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring
Jiaxin Huang, Yiqing Xie, Yu Meng +2
Taxonomy is not only a fundamental form of knowledge representation, but also crucial to vast knowledge-rich applications, such as question answering and web search. Most existing…
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning
Yuning Mao, Yanru Qu, Yiqing Xie +2
While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (M…
Guiding Corpus-based Set Expansion by Auxiliary Sets Generation and Co-Expansion
Jiaxin Huang, Yiqing Xie, Yu Meng +3
Given a small set of seed entities (e.g., ``USA'', ``Russia''), corpus-based set expansion is to induce an extensive set of entities which share the same semantic class (Country in…