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ORCIDRuchit Rawal
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2020 – today
- 2024
[c8]Ruchit Rawal, Mariya Toneva:
Perturbed examples reveal invariances shared by language models. ACL (Findings) 2024: 11564-11584- [c7]Gaurav Kumar Nayak, Inder Khatri, Ruchit Rawal, Anirban Chakraborty:
Data-free Defense of Black Box Models Against Adversarial Attacks. CVPR Workshops 2024: 254-263 - [i11]Ruchit Rawal, Khalid Saifullah, Ronen Basri, David Jacobs, Gowthami Somepalli, Tom Goldstein:
CinePile: A Long Video Question Answering Dataset and Benchmark. CoRR abs/2405.08813 (2024) - 2023
- [c6]Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva:
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. CoLLAs 2023: 601-619 - [c5]Gaurav Kumar Nayak
, Ruchit Rawal, Anirban Chakraborty:
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. WACV 2023: 4611-4620 - [i10]Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva:
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. CoRR abs/2307.06006 (2023) - [i9]Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty:
DAD++: Improved Data-free Test Time Adversarial Defense. CoRR abs/2309.05132 (2023) - [i8]Ruchit Rawal, Mariya Toneva:
Perturbed examples reveal invariances shared by language models. CoRR abs/2311.04166 (2023) - 2022
- [c4]Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty:
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CVPR Workshops 2022: 4331-4340 - [c3]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DAD: Data-free Adversarial Defense at Test Time. WACV 2022: 3788-3797 - [i7]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DAD: Data-free Adversarial Defense at Test Time. CoRR abs/2204.01568 (2022) - [i6]Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty:
Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CoRR abs/2205.02604 (2022) - [i5]Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty:
DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. CoRR abs/2210.08929 (2022) - [i4]Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty:
Data-free Defense of Black Box Models Against Adversarial Attacks. CoRR abs/2211.01579 (2022) - [i3]Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty:
Robust Few-shot Learning Without Using any Adversarial Samples. CoRR abs/2211.01598 (2022) - 2021
- [c2]Chaitra Jambigi, Ruchit Rawal, Anirban Chakraborty:
MMD-ReID: A Simple but Effective Solution for Visible-Thermal Person ReID. BMVC 2021: 116 - [i2]Chaitra Jambigi, Ruchit Rawal, Anirban Chakraborty:
MMD-ReID: A Simple but Effective Solution for Visible-Thermal Person ReID. CoRR abs/2111.05059 (2021) - 2020
- [c1]Ruchit Rawal, Prabhu Pradhan:
Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data. CVPR Workshops 2020: 350-359 - [i1]Ruchit Rawal, Prabhu Pradhan:
Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data. CoRR abs/2004.12344 (2020)
Coauthor Index
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