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Payal Bajaj
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2020 – today
- 2023
- [c15]Linyuan Gong, Chenyan Xiong, Xiaodong Liu, Payal Bajaj, Yiqing Xie, Alvin Cheung, Jianfeng Gao, Xia Song:
Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers. ACL (1) 2023: 12933-12950 - [c14]Aniket Vashishtha, S. Sai Prasad, Payal Bajaj, Vishrav Chaudhary, Kate Cook, Sandipan Dandapat, Sunayana Sitaram, Monojit Choudhury:
Performance and Risk Trade-offs for Multi-word Text Prediction at Scale. EACL (Findings) 2023: 2181-2197 - [c13]Hongyu Wang, Shuming Ma, Shaohan Huang, Li Dong, Wenhui Wang, Zhiliang Peng, Yu Wu, Payal Bajaj, Saksham Singhal, Alon Benhaim, Barun Patra, Zhun Liu, Vishrav Chaudhary, Xia Song, Furu Wei:
Magneto: A Foundation Transformer. ICML 2023: 36077-36092 - [i12]Jessica Huynh, Cathy Jiao, Prakhar Gupta, Shikib Mehri, Payal Bajaj, Vishrav Chaudhary, Maxine Eskénazi:
Understanding the Effectiveness of Very Large Language Models on Dialog Evaluation. CoRR abs/2301.12004 (2023) - [i11]Linyuan Gong, Chenyan Xiong, Xiaodong Liu, Payal Bajaj, Yiqing Xie, Alvin Cheung, Jianfeng Gao, Xia Song:
Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers. CoRR abs/2305.12567 (2023) - 2022
- [c12]Zewen Chi, Shaohan Huang, Li Dong, Shuming Ma, Bo Zheng, Saksham Singhal, Payal Bajaj, Xia Song, Xian-Ling Mao, Heyan Huang, Furu Wei:
XLM-E: Cross-lingual Language Model Pre-training via ELECTRA. ACL (1) 2022: 6170-6182 - [c11]Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul N. Bennett, Jiawei Han, Xia Song:
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators. ICLR 2022 - [c10]Zewen Chi, Li Dong, Shaohan Huang, Damai Dai, Shuming Ma, Barun Patra, Saksham Singhal, Payal Bajaj, Xia Song, Xian-Ling Mao, Heyan Huang, Furu Wei:
On the Representation Collapse of Sparse Mixture of Experts. NeurIPS 2022 - [i10]Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song:
Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators. CoRR abs/2204.03243 (2022) - [i9]Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao:
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR abs/2204.06644 (2022) - [i8]Zewen Chi, Li Dong, Shaohan Huang, Damai Dai, Shuming Ma, Barun Patra, Saksham Singhal, Payal Bajaj, Xia Song, Furu Wei:
On the Representation Collapse of Sparse Mixture of Experts. CoRR abs/2204.09179 (2022) - [i7]Hongyu Wang, Shuming Ma, Shaohan Huang, Li Dong, Wenhui Wang, Zhiliang Peng, Yu Wu, Payal Bajaj, Saksham Singhal, Alon Benhaim, Barun Patra, Zhun Liu, Vishrav Chaudhary, Xia Song, Furu Wei:
Foundation Transformers. CoRR abs/2210.06423 (2022) - 2021
- [c9]Qianlan Ying, Payal Bajaj, Budhaditya Deb, Yu Yang, Wei Wang, Bojia Lin, Milad Shokouhi, Xia Song, Yang Yang, Daxin Jiang:
Language Scaling for Universal Suggested Replies Model. NAACL-HLT (Industry Papers) 2021: 138-145 - [c8]Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song:
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining. NeurIPS 2021: 23102-23114 - [i6]Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song:
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining. CoRR abs/2102.08473 (2021) - [i5]Qianlan Ying, Payal Bajaj, Budhaditya Deb, Yu Yang, Wei Wang, Bojia Lin, Milad Shokouhi, Xia Song, Yang Yang, Daxin Jiang:
Language Scaling for Universal Suggested Replies Model. CoRR abs/2106.02232 (2021) - [i4]Zewen Chi, Shaohan Huang, Li Dong, Shuming Ma, Saksham Singhal, Payal Bajaj, Xia Song, Furu Wei:
XLM-E: Cross-lingual Language Model Pre-training via ELECTRA. CoRR abs/2106.16138 (2021)
2010 – 2019
- 2018
- [c7]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Embedding Logical Queries on Knowledge Graphs. NeurIPS 2018: 2030-2041 - [i3]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Querying Complex Networks in Vector Space. CoRR abs/1806.01445 (2018) - 2017
- [c6]Ankur Garg, Sunav Choudhary, Payal Bajaj, Sweta Agrawal, Abhishek Kedia, Shubham Agrawal:
Smart Geo-fencing with Location Sensitive Product Affinity. SIGSPATIAL/GIS 2017: 39:1-39:10 - [c5]Paroma Varma, Bryan D. He, Payal Bajaj, Nishith Khandwala, Imon Banerjee, Daniel L. Rubin, Christopher Ré:
Inferring Generative Model Structure with Static Analysis. NIPS 2017: 240-250 - [i2]Paroma Varma, Bryan D. He, Payal Bajaj, Imon Banerjee, Nishith Khandwala, Daniel L. Rubin, Christopher Ré:
Inferring Generative Model Structure with Static Analysis. CoRR abs/1709.02477 (2017) - 2016
- [c4]Payal Bajaj, Mridul Kavidayal, Priyanshu Srivastava, Md Nadeem Akhtar, Ponnurangam Kumaraguru:
Disinformation in Multimedia Annotation: Misleading Metadata Detection on YouTube. iV&L-MM@MM 2016: 53-61 - [c3]Payal Bajaj, Sumit Shekhar:
Experience Individualization on Online TV Platforms through Persona-based Account Decomposition. ACM Multimedia 2016: 252-256 - [c2]Rishabh Kaushal, Srishty Saha, Payal Bajaj, Ponnurangam Kumaraguru:
KidsTube: Detection, characterization and analysis of child unsafe content & promoters on YouTube. PST 2016: 157-164 - [i1]Rishabh Kaushal, Srishty Saha, Payal Bajaj, Ponnurangam Kumaraguru:
KidsTube: Detection, Characterization and Analysis of Child Unsafe Content & Promoters on YouTube. CoRR abs/1608.05966 (2016) - 2015
- [c1]Iftikhar Ahamath Burhanuddin, Payal Bajaj, Sumit Shekhar, Dipayan Mukherjee, Ashish Raj, Aravind Sankar:
Similarity Learning for Product Recommendation and Scoring Using Multi-channel Data. ICDM Workshops 2015: 1143-1152
Coauthor Index
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