activity
20232026
most citedContinual Named Entity Recognition without Catastrophic Forgetting

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Continual Hand-Eye Calibration for Open-world Robotic Manipulation

Fazeng Li, Gan Sun, Chenxi Liu +3

Hand-eye calibration through visual localization is a critical capability for robotic manipulation in open-world environments. However, most deep learning-based calibration models…

cs.CV2025

Revisiting Continual Semantic Segmentation with Pre-trained Vision Models

Duzhen Zhang, Yong Ren, Wei Cong +9

Continual Semantic Segmentation (CSS) seeks to incrementally learn to segment novel classes while preserving knowledge of previously encountered ones. Recent advancements in CSS ha…

cs.CV2024

Cs2K: Class-specific and Class-shared Knowledge Guidance for Incremental Semantic Segmentation

Wei Cong, Yang Cong, Yuyang Liu +1

Incremental semantic segmentation endeavors to segment newly encountered classes while maintaining knowledge of old classes. However, existing methods either 1) lack guidance from…

cs.CL2023★ 1 cited

Continual Named Entity Recognition without Catastrophic Forgetting

Duzhen Zhang, Wei Cong, Jiahua Dong +4

Continual Named Entity Recognition (CNER) is a burgeoning area, which involves updating an existing model by incorporating new entity types sequentially. Nevertheless, continual le…

cs.CL2023

Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity Recognition

Duzhen Zhang, Hongliu Li, Wei Cong +3

Incremental Named Entity Recognition (INER) involves the sequential learning of new entity types without accessing the training data of previously learned types. However, INER face…

cs.LG2023

Self-paced Weight Consolidation for Continual Learning

Wei Cong, Yang Cong, Gan Sun +2

Continual learning algorithms which keep the parameters of new tasks close to that of previous tasks, are popular in preventing catastrophic forgetting in sequential task learning…

cs.CV2023

Gradient-Semantic Compensation for Incremental Semantic Segmentation

Wei Cong, Yang Cong, Jiahua Dong +2

Incremental semantic segmentation aims to continually learn the segmentation of new coming classes without accessing the training data of previously learned classes. However, most…

cs.CV2023

Federated Incremental Semantic Segmentation

Jiahua Dong, Duzhen Zhang, Yang Cong +3

Federated learning-based semantic segmentation (FSS) has drawn widespread attention via decentralized training on local clients. However, most FSS models assume categories are fixe…