With the trend of intelligence, automobile architecture has become more complex. It is necessary to predict and discover reliability-related issues to reduce the cost of correction in the later period. In AUTOSAR-base...
详细信息
Prior foveated rendering methods often suffer from a limitation where the shading load escalates with increasing display resolution, leading to decreased efficiency, particularly when dealing with retinal-level resolu...
详细信息
As the application of smart contracts in blockchain technology becomes increasingly widespread, their security issues have emerged as a focal point of both research and practice. Although symbolic execution technology...
详细信息
Building an effective sequential recommendation system is still a challenging task due to limited interactions among users and *** work has shown the effectiveness of incorporating textual or visual information into s...
详细信息
Building an effective sequential recommendation system is still a challenging task due to limited interactions among users and *** work has shown the effectiveness of incorporating textual or visual information into sequential recommendation to alleviate the data sparse *** data sparse problem now is attracting a lot of attention in both industry and academic ***,considering interactions among modalities on a sequential scenario is an interesting yet challenging task because of multimodal *** this paper,we introduce a novel recommendation approach of considering both textual and visual information,namely Multimodal Interactive Network(MIN).The advantage of MIN lies in designing a learning framework to leverage the interactions among modalities from both the item level and the sequence level for building an efficient ***,an item-wise interactive layer based on the encoder-decoder mechanism is utilized to model the item-level interactions among modalities to select the informative ***,a sequence interactive layer based on the attention strategy is designed to capture the sequence-level preference of each *** seamlessly incorporates interactions among modalities from both the item level and the sequence level for sequential *** is the first time that interactions in each modality have been explicitly discussed and utilized in sequential *** results on four real-world datasets show that our approach can significantly outperform all the baselines in sequential recommendation task.
Concrete is a vital component in modern construction, prized for its strength, durability, and versatility. Accurately determining the quantities of concrete components is crucial in civil engineering applications to ...
详细信息
Cylindrical Algebraic Decomposition (CAD) is one of the pillar algorithms of symbolic computation, and its worst-case complexity is double exponential to the number of variables. Researchers found that variable order ...
Cylindrical Algebraic Decomposition (CAD) is one of the pillar algorithms of symbolic computation, and its worst-case complexity is double exponential to the number of variables. Researchers found that variable order dramatically affects efficiency and proposed various heuristics. The existing learning-based methods are all supervised learning methods that cannot cope with diverse polynomial sets. This paper proposes two Reinforcement Learning (RL) approaches combined with Graph Neural Networks (GNN) for Suggesting Variable Order (SVO). One is GRL-SVO(UP), a branching heuristic integrated with CAD. The other is GRL-SVO(NUP), a fast heuristic providing a total order directly. We generate a random dataset and collect a real-world dataset from SMT-LIB. The experiments show that our approaches outperform state-of-the-art learning-based heuristics and are competitive with the best expert-based heuristics. Interestingly, our models show a strong generalization ability, working well on various datasets even if they are only trained on a 3-var random dataset. The source code and data are available at https://***/dongyuhang22/GRL-SVO.
Cyber-Physical Systems (CPS) are complex systems that integrate information control devices with physical resources, which can be automatically and formalized verified by model checking according to the expected requi...
详细信息
In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutio...
详细信息
In the past decade, thanks to the powerfulness of deep-learning techniques, we have witnessed a whole new era of automated code generation. To sort out developments, we have conducted a comprehensive review of solutions to deep learning-based code generation. In this survey, we generally formalize the pipeline and procedure of code generation and categorize existing solutions according to taxonomy from perspectives of architecture, model-agnostic enhancing strategy, metrics, and tasks. In addition, we outline the challenges faced by current dominant large models and list several plausible directions for future research. We hope that this survey may provide handy guidance to understanding, utilizing, and developing deep learning-based code-generation techniques for researchers and practitioners.
In multiagent systems,agents usually do not have complete information of the whole system,which makes the analysis of such systems *** incompleteness of information is normally modelled by means of accessibility relat...
详细信息
In multiagent systems,agents usually do not have complete information of the whole system,which makes the analysis of such systems *** incompleteness of information is normally modelled by means of accessibility relations,and the schedulers consistent with such relations are called *** this paper,we consider probabilistic multiagent systems with accessibility relations and focus on the model checking problem with respect to the probabilistic epistemic temporal logic,which can specify both temporal and epistemic ***,the problem is undecidable in *** show that it becomes decidable when restricted to memoryless uniform ***,we present two algorithms for this case:one reduces the model checking problem into a mixed integer non-linear programming(MINLP)problem,which can then be solved by Satisfiability Modulo Theories(SMT)solvers,and the other is an approximate algorithm based on the upper confidence bounds applied to trees(UCT)algorithm,which can return a result whenever *** algorithms have been implemented in an existing model checker and then validated on *** experimental results show the efficiency and extendability of these algorithms,and the algorithm based on UCT outperforms the one based on MINLP in most cases.
Green characteristics are pivotal to risk transmission. We use environmental, social and governance (ESG) monetized accounting to measure green screening of stock-bond indices, and decompose risk transmission into com...
详细信息
Green characteristics are pivotal to risk transmission. We use environmental, social and governance (ESG) monetized accounting to measure green screening of stock-bond indices, and decompose risk transmission into comovement, contagion and hedging effects via a patched dependence structure model. Mechanisms through which green screening impacts three types of risk transmission effects are elucidated. Results indicate that high level of green screening is associated with significantly reduced comovement and contagion effects while hedging effects. Market sentiment factors such as interest rates, economic policy uncertainty and consumer confidence are identified as crucial channels. These results are further tested to be robust.
暂无评论