100 citations · 136 across the 11 of their papers we have counts for
12 papers
Geometric Collapse: When Vision Models Fail to Verify Physical Causality
Wentao Zhang, Jinhu Qi, Weiqiang Jin +3
Recent progress in large-scale self-supervised learning has improved dense geometric prediction, but it remains unclear whether such scaling yields inference-time physical plausibi…
RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback
Chunyu Miao, Henry Peng Zou, Yangning Li +28
Large language models (LLMs) show the promise in supporting scientific research implementation, yet their ability to generate correct and executable code remains limited. Existing…
Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning
Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King +1
Federated Unsupervised Learning (FUL) aims to learn expressive representations in federated and self-supervised settings. The quality of representations learned in FUL is usually d…
Learning Binarized Representations with Pseudo-positive Sample Enhancement for Efficient Graph Collaborative Filtering
Yankai Chen, Yue Que, Xinni Zhang +2
Learning vectorized embeddings is fundamental to many recommender systems for user-item matching. To enable efficient online inference, representation binarization, which embeds la…
Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
Dianzhi Yu, Xinni Zhang, Yankai Chen +4
Continual learning (CL) aims to empower machine learning models to learn continually from new data, while building upon previously acquired knowledge without forgetting. As models…
Towards Effective Top-N Hamming Search via Bipartite Graph Contrastive Hashing
Yankai Chen, Yixiang Fang, Yifei Zhang +3
Searching on bipartite graphs serves as a fundamental task for various real-world applications, such as recommendation systems, database retrieval, and document querying. Conventio…
A Survey on Vision-Language-Action Models for Embodied AI
Yueen Ma, Zixing Song, Yuzheng Zhuang +2
Embodied AI is widely recognized as a cornerstone of artificial general intelligence (AGI) because it involves controlling embodied agents to perform tasks in the physical world. B…
Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
Yankai Chen, Yixiang Fang, Qiongyan Wang +2
Node importance estimation problem has been studied conventionally with homogeneous network topology analysis. To deal with network heterogeneity, a few recent methods employ graph…
HiHPQ: Hierarchical Hyperbolic Product Quantization for Unsupervised Image Retrieval
Zexuan Qiu, Jiahong Liu, Yankai Chen +1
Existing unsupervised deep product quantization methods primarily aim for the increased similarity between different views of the identical image, whereas the delicate multi-level…
An Augmented Index-based Efficient Community Search for Large Directed Graphs
Yankai Chen, Jie Zhang, Yixiang Fang +2
Given a graph G and a query vertex q, the topic of community search (CS), aiming to retrieve a dense subgraph of G containing q, has gained much attention. Most existing works focu…
Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning
Yifei Zhang, Hao Zhu, Menglin Yang +4
Learning generalizable self-supervised graph representations for downstream tasks is challenging. To this end, Contrastive Learning (CL) has emerged as a leading approach. The embe…
COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
Yifei Zhang, Hao Zhu, Zixing Song +2
Graph contrastive learning (GCL) improves graph representation learning, leading to SOTA on various downstream tasks. The graph augmentation step is a vital but scarcely studied st…