WebFeb 4, 2024 · Zihang Dai, Guokun Lai, Yiming Yang, Shinjae Yoo With latent variables, stochastic recurrent models have achieved state-of-the-art performance in modeling sound-wave sequence. However, opposite results are also observed in other domains, where standard recurrent networks often outperform stochastic models. WebJul 8, 2024 · Zhiguo Wang, Haitao Mi, Wael Hamza, and Radu Florian. arXiv preprint arXiv:1612.04211. paper Natural Language Comprehension with the Epireader. Adam Trischler, Zheng Ye, Xingdi Yuan, and Kaheer Suleman. EMNLP 2016. paper Iterative Alternating Neural Attention for Machine Reading.
RACE: Large-scale ReAding Comprehension Dataset From …
WebExplainable Recommendation: A Survey and New Perspectives. arXiv Preprint 2024. arXiv:1804.11192. [2] Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu and Shaoping Ma. Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis. WebGuokun Lai. Carnegie Mellon University, Yiming Yang. Carnegie Mellon University, Quoc V. Le. Google AI Brain Team. December 2024 NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing Systems. Article. Correlation-Aware Change-Point Detection via Graph Neural Networks. aldecoaelias
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Webno code implementations • 31 Oct 2024 • Guokun Lai , Hanxiao Liu , Yiming Yang Convolution Neural Network (CNN) has gained tremendous success in computer vision … WebDec 6, 2024 · In this paper, we propose to augment the transformer architecture with an external attention mechanism to bring external knowledge and context to bear. By integrating external information into the... Web0 Guokun Lai, et al. ∙ share research ∙ 2 years ago Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing With the success of language pretraining, it is highly desirable to deve... 0 Zihang Dai, et al. ∙ share research ∙ 2 years ago Explainable Unsupervised Change-point Detection via Graph Neural Networks aldeburgh carnival programme