诱拐 发表于 2025-3-23 12:56:14
Alexander Christianial Language Processing (NLP). Recently, the Transformer structure with fully-connected self-attention blocks has been widely used in many NLP tasks due to its advantage of parallelism and global context modeling. However, in KG tasks, Transformer-based models can hardly beat the recurrent-based mode不可比拟 发表于 2025-3-23 15:01:37
Alexander Christianition capabilities. It includes two subtasks, both are used to generate commonsense knowledge expressed in natural language. The difference is that the first task is to generate commonsense using causal sentences that contain causal relationships, the second is to generate commonsense with the senten勋章 发表于 2025-3-23 18:02:19
http://reply.papertrans.cn/63/6256/625584/625584_13.pngtattle 发表于 2025-3-24 02:16:06
Alexander Christianin the sequence-to-sequence (Seq2Seq) model that applied an encoder to transform the input text into latent representation and a decoder to generate texts from the latent representation. To control the sentiment of the generated text, these models usually concatenate a disentangled feature into the l炸坏 发表于 2025-3-24 05:50:39
Alexander Christianiwo perspectives. First, adversarial training is applied to several target variables within the model, rather than only to the inputs or embeddings. We control the norm of adversarial perturbations according to the norm of original target variables, so that we can jointly add perturbations to severalflaggy 发表于 2025-3-24 09:16:53
http://reply.papertrans.cn/63/6256/625584/625584_16.pngnonchalance 发表于 2025-3-24 14:25:49
Alexander Christianiinuous vector space. Embedding methods, such as TransE, TransR and ProjE, are proposed in recent years and have achieved promising predictive performance. We discuss that a lot of substructures related with different relation properties in knowledge graph should be considered during embedding. We liALIAS 发表于 2025-3-24 15:46:01
Alexander Christianis, usually constructing a document-level graph that captures document-aware interactions, can obtain useful entity representations thus helping tackle document-level RE. These methods either focus more on the entire graph, or pay more attention to a part of the graph, e.g., paths between the targetSleep-Paralysis 发表于 2025-3-24 23:03:49
Alexander Christiani provide high-quality corpus in fields such as machine translation, structured data generation, knowledge graphs, and semantic question answering. Existing relational classification models include models based on traditional machine learning, models based on deep learning, and models based on attentGyrate 发表于 2025-3-25 02:01:59
Alexander Christianieen arguments. Previous work infuses ACCL takes external knowledge or label semantics to alleviate data scarcity, which either brings noise or underutilizes semantic information contained in label embedding. Meanwhile, it is difficult to model label hierarchy. In this paper, we make full use of labe