Payal Bajaj

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 27

Top Topics

Top Venues

NAACL-HLT (Industry Papers)

Publications

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)
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)
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)
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 (2023)
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 (2023)
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 (2022)
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)
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)
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)
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 (2022)
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 (2022)
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 (2022)
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)
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 (2021)
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 (2021)
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 (2021)
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)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Querying Complex Networks in Vector Space. CoRR (2018)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Embedding Logical Queries on Knowledge Graphs. NeurIPS (2018)
Ankur Garg, Sunav Choudhary, Payal Bajaj, Sweta Agrawal, Abhishek Kedia, Shubham Agrawal
Smart Geo-fencing with Location Sensitive Product Affinity. SIGSPATIAL/GIS (2017)
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)
Paroma Varma, Bryan D. He, Payal Bajaj, Imon Banerjee, Nishith Khandwala, Daniel L. Rubin, Christopher Ré
Inferring Generative Model Structure with Static Analysis. CoRR (2017)
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)
Payal Bajaj, Sumit Shekhar
Experience Individualization on Online TV Platforms through Persona-based Account Decomposition. ACM Multimedia (2016)
Rishabh Kaushal, Srishty Saha, Payal Bajaj, Ponnurangam Kumaraguru
KidsTube: Detection, Characterization and Analysis of Child Unsafe Content & Promoters on YouTube. CoRR (2016)
Rishabh Kaushal, Srishty Saha, Payal Bajaj, Ponnurangam Kumaraguru
KidsTube: Detection, characterization and analysis of child unsafe content & promoters on YouTube. PST (2016)
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)