8 citations · 16 across the 7 of their papers we have counts for
7 papers
Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation
Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang +6
This paper focus on few-shot object detection~(FSOD) and instance segmentation~(FSIS), which requires a model to quickly adapt to novel classes with a few labeled instances. The ex…
Self Contrastive Learning for Session-based Recommendation
Zhengxiang Shi, Xi Wang, Aldo Lipani
Session-based recommendation, which aims to predict the next item of users' interest as per an existing sequence interaction of items, has attracted growing applications of Contras…
A Survey on Asking Clarification Questions Datasets in Conversational Systems
Hossein A. Rahmani, Xi Wang, Yue Feng +3
The ability to understand a user's underlying needs is critical for conversational systems, especially with limited input from users in a conversation. Thus, in such a domain, Aski…
When and What to Ask Through World States and Text Instructions: IGLU NLP Challenge Solution
Zhengxiang Shi, Jerome Ramos, To Eun Kim +3
In collaborative tasks, effective communication is crucial for achieving joint goals. One such task is collaborative building where builders must communicate with each other to con…
MetaASSIST: Robust Dialogue State Tracking with Meta Learning
Fanghua Ye, Xi Wang, Jie Huang +3
Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general fr…
Leveraging Review Properties for Effective Recommendation
Xi Wang, Iadh Ounis, Craig Macdonald
Many state-of-the-art recommendation systems leverage explicit item reviews posted by users by considering their usefulness in representing the users' preferences and describing th…