Turn Down the Noise: Leveraging Diffusion Models for Test-time Adaptation via Pseudo-label Ensembling
Published in DistShift Workshop @ NeurIPS 2023, 2023
Mrigank Raman, Rohan Shah, Akash Kannan, Pranit Chawla
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Publications
For Distillation, Tokens Are Not All You Need
Published in Instruction Workshop @ NeurIPS 2023, 2023
Mrigank Raman, Pranav Mani, Davis Liang, Zachary Lipton
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Model-tuning Via Prompts Makes NLP Models Adversarially Robust
Published in EMNLP 2023, 2023
Mrigank Raman, Pratyush Maini, Zico Kolter, Zachary Lipton, Danish Pruthi
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Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Published in ICLR, 2021
Mrigank Raman, Aaron Chan, Siddhant Agarwal, PeiFeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, Xiang Ren
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Generalization on Unseen Domains via Inference-time Label-Preserving Target Projections
Published in CVPR (Oral), 2021
Prashant Pandey, Mrigank Raman, Sumanth Varambally, Prathosh AP
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Learning Contextualized Knowledge Structures for Commonsense Reasoning
Published in ACL-IJCNLP (Findings), 2021
Jun Yan, Mrigank Raman, Aaron Chan, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren
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Centralized active tracking of a Markov chain with unknown dynamics
Published in IEEE MASS, 2020
Mrigank Raman, Ojal Kumar, Arpan Chattotpadhyay
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