V切开 发表于 2025-3-25 05:07:27
http://reply.papertrans.cn/67/6619/661808/661808_21.pngorganic-matrix 发表于 2025-3-25 08:39:29
http://reply.papertrans.cn/67/6619/661808/661808_22.pngFID 发表于 2025-3-25 12:49:17
Co-attention and Aggregation Based Chinese Recognizing Textual Entailment Modelaggregates this feature with another feature obtained from sentences. Our model achieved 93.5% accuracy on CCL2018 textual entailment dataset, which is higher than the first place in previous evaluations. Experimental results showed that recognition of contradiction relations is difficult, but our m肮脏 发表于 2025-3-25 16:24:53
http://reply.papertrans.cn/67/6619/661808/661808_24.pngexcrete 发表于 2025-3-25 22:36:54
http://reply.papertrans.cn/67/6619/661808/661808_25.pngSeizure 发表于 2025-3-26 00:46:18
http://reply.papertrans.cn/67/6619/661808/661808_26.pngarchenemy 发表于 2025-3-26 07:08:06
http://reply.papertrans.cn/67/6619/661808/661808_27.pngdebble 发表于 2025-3-26 12:29:20
http://reply.papertrans.cn/67/6619/661808/661808_28.pngPATHY 发表于 2025-3-26 13:45:06
http://reply.papertrans.cn/67/6619/661808/661808_29.pngcarotenoids 发表于 2025-3-26 17:23:03
An Improved Class-Center Method for Text Classification Using Dependencies and WordNetdencies and the WordNet dictionary. Experiments show that, compared with traditional text classification algorithms, the improved class-center vector method has lower time complexity and higher accuracy on a large corpus.