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Titlebook: Natural Language Processing and Chinese Computing; 8th CCF Internationa Jie Tang,Min-Yen Kan,Hongying Zan Conference proceedings 2019 Sprin

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51#
發(fā)表于 2025-3-30 10:27:09 | 只看該作者
Tongxuan Zhang,Yuqi Ren,Michael Mesfin Tadessem,Bo Xu,Xikai Liu,Liang Yang,Zhihao Yang,Jian Wang,Honate rocks of Lower Cretaceous age. The lower Aptian (Gargasian) horizon contains the economically most important base metal and iron ore deposits. Subordinate ore occurrences are found in a second horizon of upper Aptian to lower Albian age. The ore deposits are found predominantly at platform margi
52#
發(fā)表于 2025-3-30 13:06:01 | 只看該作者
53#
發(fā)表于 2025-3-30 19:30:45 | 只看該作者
Yang Lin,Pengyu Huang,Yuxuan Lai,Yansong Feng,Dongyan Zhaosuspended matter (S.M.) near river mouths and, therefore, direct measurements at the river outlet do not represent real expulsions of S.M. The temperate climate, characterised by important seasonal variations throughout the year, induces significant hydrologic variations and consequently material fl
54#
發(fā)表于 2025-3-31 00:37:55 | 只看該作者
55#
發(fā)表于 2025-3-31 02:43:06 | 只看該作者
Variational Attention for Commonsense Knowledge Aware Conversation Generationponse generation, we adopt variational attention rather than standard neural attention on knowledge graphs, which is unlike previous knowledge aware generation models. Experimental results show that the variational attention based model can incorporate more clean and suitable knowledge into response generation.
56#
發(fā)表于 2025-3-31 06:44:07 | 只看該作者
57#
發(fā)表于 2025-3-31 11:48:09 | 只看該作者
58#
發(fā)表于 2025-3-31 13:46:03 | 只看該作者
Neural Response Generation with Relevant Emotions for Short Text Conversationhich train the two steps separately or jointly. An empirical study on a public dataset from STC at NTCIR-12 shows that our models outperform both a retrieval-based method and a generation model without emotion, indicating the importance of emotions in short text conversation generation and the effectiveness of our approach.
59#
發(fā)表于 2025-3-31 18:00:50 | 只看該作者
60#
發(fā)表于 2025-3-31 21:45:16 | 只看該作者
Evaluating and Enhancing the Robustness of Retrieval-Based Dialogue Systems with Adversarial Exampleess of retrieval-based dialogue systems. We conduct thorough analysis to understand the robustness of retrieval-based dialog systems. Our results provide new insights to facilitate future work on building more robust dialogue systems.
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