activity
20222026
most citedTransformer-based Reasoning for Learning Evolutionary Chain of Events on Temporal Knowledge Graph

17 citations · 35 across the 18 of their papers we have counts for

collaborators

18 papers

cs.CL2026

CHE-TKG: Collaborative Historical Evidence and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning

Shuai-long Lei, Xiaobin Zhu, Jiarui Liang +3

Temporal knowledge graph (TKG) reasoning aims to predict future events from historical facts. A key challenge lies in jointly capturing two sources of predictive information in TKG…

cs.CV2026

Probabilistic Concept Graph Reasoning for Multimodal Misinformation Detection

Ruichao Yang, Wei Gao, Xiaobin Zhu +5

Multimodal misinformation poses an escalating challenge that often evades traditional detectors, which are opaque black boxes and fragile against new manipulation tactics. We prese…

cs.AI2026

CID-TKG: Collaborative Historical Invariance and Evolutionary Dynamics Learning for Temporal Knowledge Graph Reasoning

Shuai-Long Lei, Xiaobin Zhu, Jiarui Liang +3

Temporal knowledge graph (TKG) reasoning aims to infer future facts at unseen timestamps from temporally evolving entities and relations. Despite recent progress, existing approach…

cs.LG2025

Stationarity Exploration for Multivariate Time Series Forecasting

Hao Liu, Chun Yang, Zhang xiaoxing +2

Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular fo…

cs.CV2025

Unsupervised Real-World Super-Resolution via Rectified Flow Degradation Modelling

Hongyang Zhou, Xiaobin Zhu, Liuling Chen +4

Unsupervised real-world super-resolution (SR) faces critical challenges due to the complex, unknown degradation distributions in practical scenarios. Existing methods struggle to g…

cs.CV2025

Similarity Matters: A Novel Depth-guided Network for Image Restoration and A New Dataset

Junyi He, Liuling Chen, Hongyang Zhou +5

Image restoration has seen substantial progress in recent years. However, existing methods often neglect depth information, which hurts similarity matching, results in attention di…

cs.LG2025★ 1 cited

Semantic-Enhanced Time-Series Forecasting via Large Language Models

Hao Liu, Xiaoxing Zhang, Chun Yang +1

Time series forecasting plays a significant role in finance, energy, meteorology, and IoT applications. Recent studies have leveraged the generalization capabilities of large langu…

cs.CV2025★ 1 cited

VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation

Shi-Xue Zhang, Hongfa Wang, Duojun Huang +3

Video captions play a crucial role in text-to-video generation tasks, as their quality directly influences the semantic coherence and visual fidelity of the generated videos. Altho…

cs.CV2025★ 13 cited

DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid Framework

Henrique Morimitsu, Xiaobin Zhu, Roberto M. Cesar +2

Optical flow estimation is essential for video processing tasks, such as restoration and action recognition. The quality of videos is constantly increasing, with current standards…

cs.CV2024

Video-Language Alignment via Spatio-Temporal Graph Transformer

Shi-Xue Zhang, Hongfa Wang, Xiaobin Zhu +5

Video-language alignment is a crucial multi-modal task that benefits various downstream applications, e.g., video-text retrieval and video question answering. Existing methods eith…

cs.AI2024

Arbitrary Time Information Modeling via Polynomial Approximation for Temporal Knowledge Graph Embedding

Zhiyu Fang, Jingyan Qin, Xiaobin Zhu +2

Distinguished from traditional knowledge graphs (KGs), temporal knowledge graphs (TKGs) must explore and reason over temporally evolving facts adequately. However, existing TKG app…

cs.AI2024★ 17 cited

Transformer-based Reasoning for Learning Evolutionary Chain of Events on Temporal Knowledge Graph

Zhiyu Fang, Shuai-Long Lei, Xiaobin Zhu +4

Temporal Knowledge Graph (TKG) reasoning often involves completing missing factual elements along the timeline. Although existing methods can learn good embeddings for each factual…

cs.CV2024★ 1 cited

Inverse-like Antagonistic Scene Text Spotting via Reading-Order Estimation and Dynamic Sampling

Shi-Xue Zhang, Chun Yang, Xiaobin Zhu +3

Scene text spotting is a challenging task, especially for inverse-like scene text, which has complex layouts, e.g., mirrored, symmetrical, or retro-flexed. In this paper, we propos…

cs.CV2022

Arbitrary Shape Text Detection via Segmentation with Probability Maps

Shi-Xue Zhang, Xiaobin Zhu, Lei Chen +2

Arbitrary shape text detection is a challenging task due to the significantly varied sizes and aspect ratios, arbitrary orientations or shapes, inaccurate annotations, etc. Due to…

cs.CV2022

SD-GAN: Semantic Decomposition for Face Image Synthesis with Discrete Attribute

Zhou Kangneng, Zhu Xiaobin, Gao Daiheng +3

Manipulating latent code in generative adversarial networks (GANs) for facial image synthesis mainly focuses on continuous attribute synthesis (e.g., age, pose and emotion), while…

cs.CV2022★ 2 cited

Arbitrary Shape Text Detection via Boundary Transformer

Shi-Xue Zhang, Chun Yang, Xiaobin Zhu +1

In arbitrary shape text detection, locating accurate text boundaries is challenging and non-trivial. Existing methods often suffer from indirect text boundary modeling or complex p…

cs.CV2022

Graph Fusion Network for Multi-Oriented Object Detection

Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou +1

In object detection, non-maximum suppression (NMS) methods are extensively adopted to remove horizontal duplicates of detected dense boxes for generating final object instances. Ho…

cs.CV2022

Towards Open-Set Text Recognition via Label-to-Prototype Learning

Chang Liu, Chun Yang, Hai-Bo Qin +3

Scene text recognition is a popular topic and extensively used in the industry. Although many methods have achieved satisfactory performance for the close-set text recognition chal…