activity
20162023
most citedWhen Large Language Models Meet Citation: A Survey

6 citations · 34 across the 20 of their papers we have counts for

collaborators

20 papers

cs.LG20233 cited

NPCL: Neural Processes for Uncertainty-Aware Continual Learning

Saurav Jha, Dong Gong, He Zhao +1

Continual learning (CL) aims to train deep neural networks efficiently on streaming data while limiting the forgetting caused by new tasks. However, learning transferable knowledge…

cs.CV20234 cited

Mask Propagation for Efficient Video Semantic Segmentation

Yuetian Weng, Mingfei Han, Haoyu He +4

Video Semantic Segmentation (VSS) involves assigning a semantic label to each pixel in a video sequence. Prior work in this field has demonstrated promising results by extending im…

cs.DL20236 cited

When Large Language Models Meet Citation: A Survey

Yang Zhang, Yufei Wang, Kai Wang +5

Citations in scholarly work serve the essential purpose of acknowledging and crediting the original sources of knowledge that have been incorporated or referenced. Depending on the…

cs.IR2023

Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation

Jing Du, Zesheng Ye, Bin Guo +2

Learning accurate cross-domain preference mappings in the absence of overlapped users/items has presented a persistent challenge in Non-overlapping Cross-domain Recommendation (NOC…

cs.IR2023

On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems

Xiaocong Chen, Siyu Wang, Julian McAuley +2

Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significa…

cs.HC20232 cited

Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition

Jingcheng Li, Lina Yao, Binghao Li +1

Human Activity Recognition is an important task in many human-computer collaborative scenarios, whilst having various practical applications. Although uni-modal approaches have bee…