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Multi-Variant Execution (MVX) is an effective way to detect memory corruption vulnerabilities, intrusions, or live software updates. A traditional MVX system concurrently runs multiple copies of functionally identical, layout-different program variants. ...

Knowledge graph embedding is efficient method for reasoning over known facts and inferring missing links. Existing methods are mainly triplet-based or graph-based. Triplet-based approaches learn the embedding of missing entities by a single triple only. ...

The data‐intensive research paradigm is sweeping through the scientific community, and new interaction challenges for interacting with data have emerged. Data reuse emerges as a critical driver of human‐data interaction, positioning data ...

Knowledge graph representation learning entails transforming entities and relationships within a knowledge graph into vectors to enhance downstream tasks. The rise of pre-trained language models has recently promoted text-based approaches for ...

Reinforcement learning is an algorithm that learns optimal policies through trial and error. In application domains, reinforcement learning has been successfully applied to many fields such as AlphaGo and autonomous driving systems. As the ...

There is a rising interest in exploiting aggregate information from external medical studies to enhance the statistical analysis of a modestly sized internal dataset. Currently available software packages for analyzing ...

• Provide efficient information synthesis approach under the mixture cure models.
• Synthesize subgroup survival probabilities at multiple time points.
• Rely on the computational control variate technique.
• Automatically carry out ...

Knowledge graphs are multi-relation heterogeneous graphs. Thus, the existence of numerous multi-relation entities imposes a tough challenge to the modelling of the knowledge graph. Some recent works represent the property of corresponding ...

Review is an essential piece of information that influences users’ decisions, but excessively long reviews not only degrade the user experience but also affect the accuracy of the recommender system. Therefore, Joint Inter-Word and Inter-Sentence ...

• We propose proposes summary-based recommender system (MRSR), which effectively mitigates the issue of long-text dependence by Transformer.
• The design of inter-word and inter-sentence the multi-relation modeling module aims to extract ...

Head pose estimation plays a pivotal role in various applications, including augmented reality and human–computer interaction within intelligent museum environments. Head pose estimation conventionally relies on hard labels. However, acquiring ...

Fracture distribution plays a significant role in the behavior of subsurface environments, affecting such activities as geothermal production, exploitation and management of groundwater resources, and long-term storage of nuclear waste and carbon ...

• We present tools for estimation of statistical properties of fracture networks from cross-hole tests.
• Particle-based algorithms are used to generate synthetic data for deep neural network (DNN) training.
• Regionalized training ...

Software is becoming increasingly complex and feature-rich, yet only part of any given codebase is frequently used. Existing software customization and debloating approaches target static binaries, focusing on feature discovery, control-flow analysis, ...

Abstract-Modern data centers need to keep servers running stably for a long time without affecting data integrity. Therefore, data center servers need a set of effective systematic design solutions to ensure the reliability, availability and ...

Commentaries are derivative texts formed by commentators' interpretations of classics texts, which not only reflect the commentators' understanding and values in their era but also play an irreplaceable role in contemporary people's ...

In biomedical and clinical research, predicting the survival probabilities for patients is a core task. Accurate survival probability predictions can help physicians make better treatments or prevention plans for patients. A novel ...

Linux eBPF allows a userspace application to execute code inside the Linux kernel without modifying the kernel code or inserting a kernel module. An in-kernel eBPF verifier pre-verifies any untrusted eBPF bytecode before running it in kernel context. ...

Graph neural networks (GNN) have shown great application potential in scientific research applications, biomedicine, and other fields, which exhibit superior feature representation capabilities for graph data with non-Euclidean structures. These ...

[Objective] This paper presents an overview introduction of the VenusAI platform, focusing on its technical updates and sharing the experiences gained since its deployment. The objective is to highlight the platform's advancements, challenges, and ...

[Objective] Currently, large language model (LLM) is one of research highlights in the field of natural language processing. This paper selected some open-source LLMs for deployment and comparison from the perspective of consumer-grade GPU and ...

Facial expression recognition (FER) task in the wild is challenging due to some uncertainties, such as the ambiguity of facial expressions, subjective annotations, and low-quality facial images. A novel model for FER in-the-wild ...

Knowledge graphs are sizeable graph-structured knowledge with both abstract and concrete concepts in the form of entities and relations. Recently, convolutional neural networks have achieved outstanding results for more expressive representations ...

• We propose a knowledge graph embedding model with attention-based high-low level feature interaction convolutional network.
• A criss-cross attention mechanism based on consecutive sparsely-connected graphs is introduced to our model.