27 citations · 66 across the 18 of their papers we have counts for
18 papers
Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification
Haocong Rao, Chunyan Miao
Person re-identification (re-ID) via 3D skeleton data is a challenging task with significant value in many scenarios. Existing skeleton-based methods typically assume virtual motio…
A Survey of Artificial Intelligence in Gait-Based Neurodegenerative Disease Diagnosis
Haocong Rao, Minlin Zeng, Xuejiao Zhao +1
Recent years have witnessed an increasing global population affected by neurodegenerative diseases (NDs), which traditionally require extensive healthcare resources and human effor…
A Survey on 3D Skeleton Based Person Re-Identification: Taxonomy, Advances, Challenges, and Interdisciplinary Prospects
Haocong Rao, Chunyan Miao
Person re-identification via 3D skeletons is an important emerging research area that attracts increasing attention within the pattern recognition community. With distinctive advan…
Hierarchical Skeleton Meta-Prototype Contrastive Learning with Hard Skeleton Mining for Unsupervised Person Re-Identification
Haocong Rao, Cyril Leung, Chunyan Miao
With rapid advancements in depth sensors and deep learning, skeleton-based person re-identification (re-ID) models have recently achieved remarkable progress with many advantages.…
Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning
Ran Zhou, Xin Li, Lidong Bing +2
In cross-lingual named entity recognition (NER), self-training is commonly used to bridge the linguistic gap by training on pseudo-labeled target-language data. However, due to sub…
TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification
Haocong Rao, Chunyan Miao
Person re-identification (re-ID) via 3D skeleton data is an emerging topic with prominent advantages. Existing methods usually design skeleton descriptors with raw body joints or p…
History-Aware Hierarchical Transformer for Multi-session Open-domain Dialogue System
Tong Zhang, Yong Liu, Boyang Li +5
With the evolution of pre-trained language models, current open-domain dialogue systems have achieved great progress in conducting one-session conversations. In contrast, Multi-Ses…
Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer
Zhixiang Su, Di Wang, Chunyan Miao +1
Recent studies on knowledge graphs (KGs) show that path-based methods empowered by pre-trained language models perform well in the provision of inductive and explainable relation p…
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
Qihuang Zhong, Liang Ding, Yibing Zhan +11
This technical report briefly describes our JDExplore d-team's Vega v2 submission on the SuperGLUE leaderboard. SuperGLUE is more challenging than the widely used general language…
ConNER: Consistency Training for Cross-lingual Named Entity Recognition
Ran Zhou, Xin Li, Lidong Bing +3
Cross-lingual named entity recognition (NER) suffers from data scarcity in the target languages, especially under zero-shot settings. Existing translate-train or knowledge distilla…
Exploring Representation-Level Augmentation for Code Search
Haochen Li, Chunyan Miao, Cyril Leung +4
Code search, which aims at retrieving the most relevant code fragment for a given natural language query, is a common activity in software development practice. Recently, contrasti…
ManiCLIP: Multi-Attribute Face Manipulation from Text
Hao Wang, Guosheng Lin, Ana García del Molino +3
In this paper we present a novel multi-attribute face manipulation method based on textual descriptions. Previous text-based image editing methods either require test-time optimiza…
Skeleton Prototype Contrastive Learning with Multi-Level Graph Relation Modeling for Unsupervised Person Re-Identification
Haocong Rao, Chunyan Miao
Person re-identification (re-ID) via 3D skeletons is an important emerging topic with many merits. Existing solutions rarely explore valuable body-component relations in skeletal s…
Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval
Hao Wang, Guosheng Lin, Steven C. H. Hoi +1
This paper investigates an open research problem of generating text-image pairs to improve the training of fine-grained image-to-text cross-modal retrieval task, and proposes a nov…
3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image
Hao Wang, Wenhao Shen, Guosheng Lin +2
In this paper, we investigate an open research task of generating 3D cartoon face shapes from single 2D GAN generated human faces and without 3D supervision, where we can also mani…
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER
Ran Zhou, Xin Li, Ruidan He +4
Data augmentation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as NER, data augmentation methods often suffe…
Towards Persona-Based Empathetic Conversational Models
Peixiang Zhong, Chen Zhang, Hao Wang +2
Empathetic conversational models have been shown to improve user satisfaction and task outcomes in numerous domains. In Psychology, persona has been shown to be highly correlated t…
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition
Shengfei Lyu, Linghao Sun, Huixiong Yi +3
In recent years, great success has been achieved in many tasks of natural language processing (NLP), e.g., named entity recognition (NER), especially in the high-resource language,…