Prateek Yadav

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 34

Top Topics

Code Generation

Link Prediction

Graph Mining Algorithms

Supervised Classification

Top Venues

Publications

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 (2024)
Prateek Yadav, Peter Hase, Mohit Bansal
INSPIRE: Incorporating Diverse Feature Preferences in Recourse. Trans. Mach. Learn. Res. 2024 (2024)
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 (2024)
Adyasha Maharana, Prateek Yadav, Mohit Bansal
D2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning. ICLR (2024)
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) (2024)
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)
Prateek Yadav, Mohit Bansal
Exclusive Supermask Subnetwork Training for Continual Learning. ACL (Findings) (2023)
Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization. CoRR (2023)
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 (2023)
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 (2023)
Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal
TIES-Merging: Resolving Interference When Merging Models. NeurIPS (2023)
Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal
Self-Chained Image-Language Model for Video Localization and Question Answering. NeurIPS (2023)
Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal
Resolving Interference When Merging Models. CoRR (2023)
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)
Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal
Self-Chained Image-Language Model for Video Localization and Question Answering. CoRR (2023)
Adyasha Maharana, Prateek Yadav, Mohit Bansal
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning. CoRR (2023)
Prateek Yadav, Mohit Bansal
Exclusive Supermask Subnetwork Training for Continual Learning. CoRR (2022)
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning. CoRR (2022)
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning. ACL (1) (2022)
Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. CoRR (2021)
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning. CoRR (2021)
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning. NAACL-HLT (2021)
Prateek Yadav, Peter Hase, Mohit Bansal
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions. CoRR (2021)
Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning. EMNLP (1) (2021)
Naganand Yadati, Vikram Nitin, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha P. Talukdar
NHP: Neural Hypergraph Link Prediction. CIKM (2020)
Prateek Yadav, Subrat Kar
Evaluating the Impact of Region Based Content Popularity of Videos on the Cost of CDN Deployment. NCC (2020)
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Pratim Talukdar
Lovasz Convolutional Networks. AISTATS (2019)
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)
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning. AISTATS (2019)
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning. CoRR (2019)
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)
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha Pratim Talukdar
HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification. CoRR (2018)
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar
Graph Convolutional Networks based Word Embeddings. CoRR (2018)
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Arun Rajkumar, Partha Pratim Talukdar
Lovasz Convolutional Networks. CoRR (2018)