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ORCIDPrateek Yadav
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2020 – today
- 2024
[j3]Prateek Yadav
, Subrat Kar:
Efficient Content Distribution in Fog-Based CDN: A Joint Optimization Algorithm for Fog-Node Placement and Content Delivery. IEEE Internet Things J. 11(9): 16578-16590 (2024)- [j2]Prateek Yadav, Subrat Kar:
A cost-efficient content distribution optimization model for fog-based content delivery networks. J. Cloud Comput. 13(1): 141 (2024) - [j1]Prateek Yadav, Peter Hase, Mohit Bansal:
INSPIRE: Incorporating Diverse Feature Preferences in Recourse. Trans. Mach. Learn. Res. 2024 (2024) - [c15]Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen:
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. ICLR 2024 - [c14]Adyasha Maharana, Prateek Yadav, Mohit Bansal:
D2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning. ICLR 2024 - [i20]Taishi Nakamura, Mayank Mishra, Simone Tedeschi, Yekun Chai, Jason T. Stillerman, Felix Friedrich, Prateek Yadav, Tanmay Laud, Minh Chien Vu, Terry Yue Zhuo, Diganta Misra, Ben Bogin, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Junior, Alpay Ariyak, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Noah Persaud, Nour Moustafa-Fahmy, Tianlong Chen, Mohit Bansal, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Huu Nguyen, Sampo Pyysalo:
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. CoRR abs/2404.00399 (2024) - [i19]Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, Thong Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, David Lo, Binyuan Hui, Niklas Muennighoff, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro von Werra:
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions. CoRR abs/2406.15877 (2024) - [i18]Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni:
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning. CoRR abs/2408.07057 (2024) - [i17]Prateek Yadav, Tu Vu, Jonathan Lai, Alexandra Chronopoulou, Manaal Faruqui, Mohit Bansal, Tsendsuren Munkhdalai:
What Matters for Model Merging at Scale? CoRR abs/2410.03617 (2024) - [i16]Pingzhi Li, Prateek Yadav, Jaehong Yoon, Jie Peng, Yi-Lin Sung, Mohit Bansal, Tianlong Chen:
Glider: Global and Local Instruction-Driven Expert Router. CoRR abs/2410.07172 (2024) - 2023
- [c13]Prateek Yadav, Mohit Bansal:
Exclusive Supermask Subnetwork Training for Continual Learning. ACL (Findings) 2023: 569-587 - [c12]Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Parminder Bhatia, Xiaofei Ma, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang:
Exploring Continual Learning for Code Generation Models. ACL (2) 2023: 782-792 - [c11]Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal:
TIES-Merging: Resolving Interference When Merging Models. NeurIPS 2023 - [c10]Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal:
Self-Chained Image-Language Model for Video Localization and Question Answering. NeurIPS 2023 - [i15]Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal:
Self-Chained Image-Language Model for Video Localization and Question Answering. CoRR abs/2305.06988 (2023) - [i14]Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal:
Resolving Interference When Merging Models. CoRR abs/2306.01708 (2023) - [i13]Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Xiaofei Ma, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang:
Exploring Continual Learning for Code Generation Models. CoRR abs/2307.02435 (2023) - [i12]Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen:
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. CoRR abs/2310.01334 (2023) - [i11]Adyasha Maharana, Prateek Yadav, Mohit Bansal:
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning. CoRR abs/2310.07931 (2023) - [i10]Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal:
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization. CoRR abs/2311.13171 (2023) - 2022
- [c9]Swarnadeep Saha, Prateek Yadav, Mohit Bansal:
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning. ACL (1) 2022: 1190-1208 - [i9]Swarnadeep Saha, Prateek Yadav, Mohit Bansal:
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning. CoRR abs/2204.04813 (2022) - [i8]Prateek Yadav, Mohit Bansal:
Exclusive Supermask Subnetwork Training for Continual Learning. CoRR abs/2210.10209 (2022) - 2021
- [c8]Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal:
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. EMNLP (1) 2021: 7716-7740 - [c7]Swarnadeep Saha, Prateek Yadav, Mohit Bansal:
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning. NAACL-HLT 2021: 3662-3677 - [i7]Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal:
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. CoRR abs/2104.07644 (2021) - [i6]Swarnadeep Saha, Prateek Yadav, Mohit Bansal:
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning. CoRR abs/2106.01354 (2021) - [i5]Prateek Yadav, Peter Hase, Mohit Bansal:
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions. CoRR abs/2111.01235 (2021) - 2020
- [c6]Naganand Yadati, Vikram Nitin, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha P. Talukdar:
NHP: Neural Hypergraph Link Prediction. CIKM 2020: 1705-1714 - [c5]Prateek Yadav, Subrat Kar:
Evaluating the Impact of Region Based Content Popularity of Videos on the Cost of CDN Deployment. NCC 2020: 1-6
2010 – 2019
- 2019
- [c4]Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar:
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks. ACL (1) 2019: 3308-3318 - [c3]Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar:
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning. AISTATS 2019: 1792-1801 - [c2]Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Pratim Talukdar:
Lovasz Convolutional Networks. AISTATS 2019: 1978-1987 - [c1]Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, Partha P. Talukdar:
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs. NeurIPS 2019: 1509-1520 - [i4]Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar:
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning. CoRR abs/1901.08255 (2019) - 2018
- [i3]Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Arun Rajkumar, Partha Pratim Talukdar:
Lovasz Convolutional Networks. CoRR abs/1805.11365 (2018) - [i2]Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha Pratim Talukdar:
HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. CoRR abs/1809.02589 (2018) - [i1]Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar:
Graph Convolutional Networks based Word Embeddings. CoRR abs/1809.04283 (2018)
Coauthor Index
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