Graph-based reasoning over heterogeneous
WebApr 7, 2024 · Section 3 presents the materials and methods of this paper. Section 4 is the implementation of the knowledge graph. Section 5 describes the design of knowledge reasoning rules. Section 6 presents an experimental analysis of road renewal decision-making. Section 7 is the conclusion of this paper. Websince it requires an adequate comprehension of the whole document and the multi-hop reasoning ability across multiple sentences to reach the final result. In this paper, we propose a novel graph-based model with Dual-tier Heterogeneous Graph (DHG) for document-level RE. In particular,
Graph-based reasoning over heterogeneous
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WebA tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. WebSep 9, 2024 · Download a PDF of the paper titled Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering, by …
WebOct 21, 2024 · Recent years, the research on graph-based reasoning has received widespread attention because reasoning is an important form of simulated thinking, which can deduce some conclusions from existing knowledge. ... We conduct a random walk over heterogeneous network by probabilistically selecting next node v i + 1 from a current … WebTraditional neural networks have limited capabilities in modeling the refined global and contextual semantics of emotional texts and usually ignore the dependencies between different emotional words. To address this limitation, this paper proposes a construction-assisted multi-scale graph reasoning network (ConAs-GRNs), which explores the …
WebSep 29, 2024 · Document-level relation extraction aims to extract relations among entities within a document. Different from sentence-level relation extraction, it requires reasoning over multiple sentences across a document. In this paper, we propose Graph Aggregation-and-Inference Network (GAIN) featuring double graphs. GAIN first constructs a … WebSep 9, 2024 · We propose a version of graph convolutional networks (GCNs), a recent class of multilayer neural networks operating on graphs, suited to modeling syntactic dependency graphs. GCNs over syntactic ...
WebExperimental results on CommonsenseQA dataset illustrate that our graph-based approach over both knowledge sources brings improvement over strong baselines. Our approach achieves the state-of-the-art accuracy (75.3%) on the CommonsenseQA leaderboard. ... Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense …
WebAug 26, 2024 · Automatic fact verification (FV) based on artificial intelligence is considered as a promising approach which can be used to identify misinformation distributed on the web. Even though previous FV using deep learning have made great achievements in single dataset (e.g., FEVER), the trained systems are unlikely to be capable of extracting … cincinnati bengals special teams coachWebMay 17, 2024 · Multi-hop reading comprehension (RC) across documents poses new challenge over single-document RC because it requires reasoning over multiple documents to reach the final answer. In this paper, we propose a new model to tackle the multi-hop RC problem. We introduce a heterogeneous graph with different types of … cincinnati bengals starting lineup todayWebWith the two-level attention mechanism, IARNet can aggregate multi-type information in a hierarchical manner and the information can reason over heterogeneous graph for the facticity of the news. Experimental result shows that our method outperforms the state-of-the-art competitors on real-world datasets with GloVe embeddings. cincinnati bengals stadium seating capacityWebOct 12, 2024 · @inproceedings{lv2024commonsense, author = {Shangwen Lv, Daya Guo, Jingjing Xu, Duyu Tang, Nan Duan, Ming Gong, Linjun Shou, Daxin Jiang, Guihong Cao and Songlin Hu}, title = {Graph-Based … cincinnati bengals sports memorabiliaWebDec 26, 2024 · Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks: IJCAI 2024: Link- ... Reinforcement Learning Enhanced Heterogeneous Graph Neural Network: arXiv: Link: Link: 2024. Year Title Venue ... Hierarchical Reinforcement Learning for Knowledge … dhs commonwealthWebMay 17, 2024 · We introduce the HDE graph, a heterogeneous graph for multiple-hop reasoning over nodes representing different granularity levels of information. We use co-attention and self-attention to encode candidates, documents, entities of mentions of candidates and query subjects into query-aware representations, which are then … dhs community connect north dakotaWebWith the two-level attention mechanism, IARNet can aggregate multi-type information in a hierarchical manner and the information can reason over heterogeneous graph for the … dhs committee members