Auto Encoder: How to Ignore the Signal Noise

Authors: (1) Tony Lee, Stanford with Equal contribution; (2) Michihiro Yasunaga, Stanford with Equal contribution; (3) Chenlin Meng, Stanford with Equal contribution; (4) Yifan Mai, Stanford; (5) Joon Sung Park, Stanford; (6) Agrim Gupta, Stanford; (7) Yunzhi Zhang, Stanford; (8) Deepak Narayanan, Microsoft; (9) Hannah Benita Teufel, Aleph Alpha; (10) Marco Bellagente, Aleph Alpha; (11) Minguk Kang, POSTECH; (12) Taesung Park, Adobe; (13) Jure Leskovec, Stanford; (14) Jun-Yan Zhu, CMU; (15) Li Fei-Fei, Stanford; (16)

Authors: (1) Tony Lee, Stanford with Equal contribution; (2) Michihiro Yasunaga, Stanford with Equal contribution; (3) Chenlin Meng, Stanford with Equal contribution; (4) Yifan Mai, Stanford; (5) Joon Sung Park, Stanford; (6) Agrim Gupta, Stanford; (7) Yunzhi Zhang, Stanford; (8) Deepak Narayanan, Microsoft; (9) Hannah Benita Teufel, Aleph Alpha; (10) Marco Bellagente, Aleph Alpha; (11) Minguk Kang, POSTECH; (12) Taesung Park, Adobe; (13) Jure Leskovec, Stanford; (14) Jun-Yan Zhu, CMU; (15) Li Fei-Fei, Stanford; (16)

Authors: (1) Liang Wang, Microsoft Corporation, and Correspondence to ([email protected]); (2) Nan Yang, Microsoft Corporation, and correspondence to ([email protected]); (3) Xiaolong Huang, Microsoft Corporation; (4) Linjun Yang, Microsoft Corporation; (5) Rangan Majumder, Microsoft Corporation; (6) Furu Wei, Microsoft Corporation and Correspondence to ([email protected]). The model and dataset release information is available at https://github.com/microsoft/ unilm/tree/master/e5.

Authors: (1) Liang Wang, Microsoft Corporation, and Correspondence to ([email protected]); (2) Nan Yang, Microsoft Corporation, and correspondence to ([email protected]); (3) Xiaolong Huang, Microsoft Corporation; (4) Linjun Yang, Microsoft Corporation; (5) Rangan Majumder, Microsoft Corporation; (6) Furu Wei, Microsoft Corporation and Correspondence to ([email protected]). Table of Links Abstract and 1 Introduction 2 Related Work 3 Method 3.1 Synthetic Data Generation 3.2 Training 4 Experiments 4.1 Statistics of the Synthetic Data 4.2 Model Fine-tuning and Evaluation 4.3

Authors: (1) Thuat Nguyen, Dept. of Computer Science, University of Oregon, OR, USA; (2) Chien Van Nguyen, Dept. of Computer Science, University of Oregon, OR, USA; (3) Viet Dac Lai, Dept. of Computer Science, University of Oregon, OR, USA; (4) Hieu Man, Dept. of Computer Science, University of Oregon, OR, USA; (5) Nghia Trung Ngo, Dept. of Computer Science, University of Oregon, OR, USA; (6) Franck Dernoncourt, Adobe Research, USA; (7) Ryan A. Rossi, Adobe