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ORCIDArnav Chavan
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2020 – today
- 2024
[c13]Arnav Chavan, Nahush Lele, Deepak K. Gupta:
Surgical Feature-Space Decomposition of LLMs: Why, When and How? ACL (1) 2024: 2389-2400- [c12]Arnav Chavan, Nahush Lele, Deepak K. Gupta:
Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models. Tiny Papers @ ICLR 2024 - [c11]Akash Guna R. T., Arnav Chavan, Deepak K. Gupta:
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. Tiny Papers @ ICLR 2024 - [c10]Arnav Chavan, Raghav Magazine, Shubham Kushwaha, Mérouane Debbah, Deepak K. Gupta:
Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward. IJCAI 2024: 7980-7988 - [i14]Arnav Chavan, Raghav Magazine, Shubham Kushwaha, Mérouane Debbah, Deepak K. Gupta:
Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward. CoRR abs/2402.01799 (2024) - [i13]Akash Guna R. T., Arnav Chavan, Deepak K. Gupta:
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. CoRR abs/2402.12418 (2024) - [i12]Arnav Chavan, Nahush Lele, Deepak K. Gupta:
Surgical Feature-Space Decomposition of LLMs: Why, When and How? CoRR abs/2405.13039 (2024) - 2023
- [c9]Krithika Ramesh, Arnav Chavan, Shrey Pandit, Sunayana Sitaram:
A Comparative Study on the Impact of Model Compression Techniques on Fairness in Language Models. ACL (1) 2023: 15762-15782 - [c8]Saksham Aggarwal, Taneesh Gupta, Pawan Kumar Sahu, Arnav Chavan, Rishabh Tiwari, Dilip K. Prasad, Deepak K. Gupta:
On Designing Light-Weight Object Trackers Through Network Pruning: Use CNNS or Transformers? ICASSP 2023: 1-5 - [c7]Rishabh Tiwari, Arnav Chavan, Deepak K. Gupta, Gowreesh Mago, Animesh Gupta, Akash Gupta, Suraj Sharan, Yukun Yang, Shanwei Zhao, Shihao Wang, Youngjun Kwak, Seonghun Jeong, Yunseung Lee, Changick Kim, Subin Kim, Ganzorig Gankhuyag, Ho Jung, Junwhan Ryu, HaeMoon Kim, Byeong Hak Kim, Tu Vo, Sheir Zaheer, Alexander Holston, Chan Y. Park, Dheemant Dixit, Nahush Lele, Kushagra Bhushan, Debjani Bhowmick, Devanshu Arya, Sadaf Gulshad, Amirhossein Habibian, Amir Ghodrati, Babak Ehteshami Bejnordi, Jai Gupta, Zhuang Liu, Jiahui Yu, Dilip K. Prasad, Zhiqiang Shen:
RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning. ICCV (Workshops) 2023: 1526-1535 - [i11]Deepak K. Gupta, Gowreesh Mago, Arnav Chavan, Dilip K. Prasad:
Patch Gradient Descent: Training Neural Networks on Very Large Images. CoRR abs/2301.13817 (2023) - [i10]Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen:
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR abs/2306.07967 (2023) - [i9]Arnav Chavan, Nahush Lele, Deepak K. Gupta:
Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models. CoRR abs/2312.07046 (2023) - 2022
- [c6]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR 2022: 4921-4931 - [c5]Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta:
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning. CVPR 2022: 9841-9850 - [c4]Oliver Rippel, Arnav Chavan, Chucai Lei, Dorit Merhof:
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations. IMPROVE 2022: 45-56 - [i8]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR abs/2201.00814 (2022) - [i7]Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta:
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning. CoRR abs/2206.01690 (2022) - [i6]Saksham Aggarwal, Taneesh Gupta, Pawan Kumar Sahu, Arnav Chavan, Rishabh Tiwari, Dilip K. Prasad, Deepak K. Gupta:
On designing light-weight object trackers through network pruning: Use CNNs or transformers? CoRR abs/2211.13769 (2022) - 2021
- [j1]Sharib Ali
, Mariia Dmitrieva, Noha M. Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan J. Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Lê Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James E. East, Jens Rittscher:
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Anal. 70: 102002 (2021) - [c3]Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta:
Rescaling CNN Through Learnable Repetition of Network Parameters. ICIP 2021: 754-758 - [c2]Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta:
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations. ICLR 2021 - [i5]Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta:
Rescaling CNN through Learnable Repetition of Network Parameters. CoRR abs/2101.05650 (2021) - [i4]Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta:
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations. CoRR abs/2102.07156 (2021) - [i3]Oliver Rippel, Arnav Chavan, Chucai Lei, Dorit Merhof:
Transfer Learning Gaussian Anomaly Detection by Fine-Tuning Representations. CoRR abs/2108.04116 (2021) - 2020
- [c1]Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj:
Multi-plateau Ensemble For Endoscopic Artefact Segmentation And Detection. EndoCV@ISBI 2020: 22-25 - [i2]Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj:
Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection. CoRR abs/2003.10129 (2020) - [i1]Sharib Ali, Mariia Dmitrieva, Noha M. Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan J. Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Lê Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James E. East, Jens Rittscher:
A translational pathway of deep learning methods in GastroIntestinal Endoscopy. CoRR abs/2010.06034 (2020)
Coauthor Index
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