Prateek Yadav

45 papers A* 7A 3Journal 27Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning.
Trans. Mach. Learn. Res.
Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni
2025 — conf
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code.
COLING (Industry)
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 Barbosa Junior, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Nour Moustafa-Fahmy, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Hiep Nguyen, Sampo Pyysalo
2025 A* conf
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.
ICLR
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, James Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, et al.
2025 J jnl
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization.
Trans. Mach. Learn. Res.
Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal
2025 A* conf
Glider: Global and Local Instruction-Driven Expert Router.
EMNLP
Pingzhi Li, Prateek Yadav, Jaehong Yoon, Jie Peng, Yi-Lin Sung, Mohit Bansal, Tianlong Chen
2025 J jnl
RSQ: Learning from Important Tokens Leads to Better Quantized LLMs.
CoRR
Yi-Lin Sung, Prateek Yadav, Jialu Li, Jaehong Yoon, Mohit Bansal
2025 J jnl
What Matters for Model Merging at Scale?
Trans. Mach. Learn. Res.
Prateek Yadav, Tu Vu, Jonathan Lai, Alexandra Chronopoulou, Manaal Faruqui, Mohit Bansal, Tsendsuren Munkhdalai
2024 J jnl
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning.
CoRR
Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni
2024 J jnl
A cost-efficient content distribution optimization model for fog-based content delivery networks.
J. Cloud Comput.
Prateek Yadav, Subrat Kar
2024 J jnl
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order.
CoRR
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 Barbosa 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
2024 J jnl
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.
CoRR
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
2024 A* conf
D2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning.
ICLR
Adyasha Maharana, Prateek Yadav, Mohit Bansal
2024 J jnl
Efficient Content Distribution in Fog-Based CDN: A Joint Optimization Algorithm for Fog-Node Placement and Content Delivery.
IEEE Internet Things J.
Prateek Yadav, Subrat Kar
2024 J jnl
Glider: Global and Local Instruction-Driven Expert Router.
CoRR
Pingzhi Li, Prateek Yadav, Jaehong Yoon, Jie Peng, Yi-Lin Sung, Mohit Bansal, Tianlong Chen
2024 J jnl
INSPIRE: Incorporating Diverse Feature Preferences in Recourse.
Trans. Mach. Learn. Res.
Prateek Yadav, Peter Hase, Mohit Bansal
2024 A* conf
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy.
ICLR
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen
2024 J jnl
What Matters for Model Merging at Scale?
CoRR
Prateek Yadav, Tu Vu, Jonathan Lai, Alexandra Chronopoulou, Manaal Faruqui, Mohit Bansal, Tsendsuren Munkhdalai
2023 J jnl
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization.
CoRR
Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal
2023 J jnl
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning.
CoRR
Adyasha Maharana, Prateek Yadav, Mohit Bansal
2023 — conf
Exclusive Supermask Subnetwork Training for Continual Learning.
ACL (Findings)
Prateek Yadav, Mohit Bansal
2023 — conf
Exploring Continual Learning for Code Generation Models.
ACL (2)
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
2023 J jnl
Exploring Continual Learning for Code Generation Models.
CoRR
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
2023 J jnl
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy.
CoRR
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen
2023 J jnl
Resolving Interference When Merging Models.
CoRR
Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal
2023 A* conf
Self-Chained Image-Language Model for Video Localization and Question Answering.
NeurIPS
Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal
2023 J jnl
Self-Chained Image-Language Model for Video Localization and Question Answering.
CoRR
Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal
2023 A* conf
TIES-Merging: Resolving Interference When Merging Models.
NeurIPS
Prateek Yadav, Derek Tam, Leshem Choshen, Colin A. Raffel, Mohit Bansal
2022 J jnl
Exclusive Supermask Subnetwork Training for Continual Learning.
CoRR
Prateek Yadav, Mohit Bansal
2022 — conf
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning.
ACL (1)
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
2022 J jnl
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning.
CoRR
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
2021 — conf
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning.
EMNLP (1)
Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal
2021 J jnl
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning.
CoRR
Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal
2021 J jnl
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions.
CoRR
Prateek Yadav, Peter Hase, Mohit Bansal
2021 — conf
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning.
NAACL-HLT
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
2021 J jnl
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning.
CoRR
Swarnadeep Saha, Prateek Yadav, Mohit Bansal
2020 — conf
Evaluating the Impact of Region Based Content Popularity of Videos on the Cost of CDN Deployment.
NCC
Prateek Yadav, Subrat Kar
2020 A conf
NHP: Neural Hypergraph Link Prediction.
CIKM
Naganand Yadati, Vikram Nitin, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha P. Talukdar
2019 A conf
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning.
AISTATS
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar
2019 J jnl
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning.
CoRR
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Partha P. Talukdar
2019 A* conf
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs.
NeurIPS
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, Partha P. Talukdar
2019 — conf
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks.
ACL (1)
Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar
2019 A conf
Lovasz Convolutional Networks.
AISTATS
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Shikhar Vashishth, Arun Rajkumar, Partha Pratim Talukdar
2018 J jnl
Graph Convolutional Networks based Word Embeddings.
CoRR
Shikhar Vashishth, Prateek Yadav, Manik Bhandari, Piyush Rai, Chiranjib Bhattacharyya, Partha P. Talukdar
2018 J jnl
HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification.
CoRR
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Anand Louis, Partha Pratim Talukdar
2018 J jnl
Lovasz Convolutional Networks.
CoRR
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati, Arun Rajkumar, Partha Pratim Talukdar