Zhao Zhang

Compressing Knowledge Graph Embedding with Relational Graph Auto-encoder

2020

Knowledge graphs (KGs) are extremely useful resources for varieties of applications. However, with the large and steadily growing sizes of modern KGs, knowledge graph embeddings (KGE), which represent entities and relations in KGs into 32-bit …

MDPL-net: Multi-layer Dictionary Learning Network with Added Skip Dense Connections

2020

Dictionary learning (DL) is powerful for representation learning, while it fails to capture the deep hierarchical information hidden in data. In this paper, we propose a new generalized end-to-end mulita-layer representation learning architecture referred to …

Towards Robust Knowledge Graph Embedding via Multi-Task Reinforcement Learning

2021 · IEEE Transactions on Knowledge and Data Engineering

Nowadays, Knowledge graphs (KGs) have been playing a pivotal role in AI-related applications. Despite the large sizes, existing KGs are far from complete and comprehensive. In order to continuously enrich KGs, automatic knowledge construction and …

Along the Time

2022 · Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Recent years have witnessed remarkable progress on knowledge graph embedding (KGE) methods to learn the representations of entities and relations in static knowledge graphs (SKGs). However, knowledge changes over time. In order to represent the …

Attacking Pre-trained Recommendation

2023

Recently, a series of pioneer studies have shown the potency of pre-trained models in sequential recommendation, illuminating the path of building an omniscient unified pre-trained recommendation model for different downstream recommendation tasks. Despite these advancements, …

Multi-round Counterfactual Generation: Interpreting and Improving Models of Text Classification

2024

In recent years, natural language processing (NLP) models have demonstrated remarkable performance in text classification tasks. However, trust in the decision-making process requires a deeper understanding of the operational principles of these networks. Therefore, there …

Recoil-free Quantum Gates with Optical Qubits

2024 · arXiv (Cornell University)

We propose a scheme to perform optical pulses that suppress the effect of photon recoil by three orders of magnitude compared to ordinary pulses in the Lamb-Dicke regime. We derive analytical insight about the fundamental …

Scheduling Data Processing Pipelines for Incremental Training on MLP-based Recommendation Models

2025

Multi-layer Perceptron (MLP)-based models have been widely exploited by modern recommendation applications. In practice, industrial recommendation scenarios frequently launch continuous incremental training jobs with only one epoch to capture real-time user features. This kind of …

Loom: A Deterministic Execution Framework Towards Nested Contract Transactions

2025

Smart contracts have expanded blockchain applications, but permissioned blockchain systems face severe through-put challenges, especially with the increasing complexity of nested contract transactions. These transactions, involving cross-contract interactions and deep call chains, intensify execution conflicts …

DPF-CM: A Data Processing Framework with Privacy-Preserving Vector Databases for Chinese Medical LLMs Training and Deployment

2025 · arXiv (Cornell University)

Current open-source training pipelines for Chinese medical language models predominantly emphasize optimizing training methodologies to enhance the performance of large language models (LLMs), yet lack comprehensive exploration into training data processing. To address this gap, …