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Deep Bidirectional Language-Knowledge Graph Pretraining


Oct 19, 2022
Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D Manning, Percy Liang, Jure Leskovec

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* Published at NeurIPS 2022. Code, data, and trained models are available at https://github.com/michiyasunaga/dragon 

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GreaseLM: Graph REASoning Enhanced Language Models for Question Answering


Jan 21, 2022
Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec

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* Published at ICLR 2022. All code, data, and pretrained models are available at https://github.com/snap-stanford/GreaseLM 

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Hierarchical Prototype Networks for Continual Graph Representation Learning


Nov 30, 2021
Xikun Zhang, Dongjin Song, Dacheng Tao

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On the Opportunities and Risks of Foundation Models


Aug 18, 2021
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

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* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 

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Do Language Embeddings Capture Scales?


Oct 11, 2020
Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, Dan Roth

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* Accepted at EMNLP Findings 2020 and EMNLP BlackboxNLP workshop 2020 

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Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks


Aug 03, 2019
Srijan Kumar, Xikun Zhang, Jure Leskovec

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* ACM SIGKDD 2019 research track oral paper. The code and datasets are available on the project website: https://github.com/srijankr/jodie/ arXiv admin note: substantial text overlap with arXiv:1812.02289 

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Learning Dynamic Embeddings from Temporal Interactions


Dec 06, 2018
Srijan Kumar, Xikun Zhang, Jure Leskovec

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Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition


May 31, 2018
Xikun Zhang, Chang Xu, Xinmei Tian, Dacheng Tao

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