Arnav Chavan

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 27

Top Topics

Continuous Optimization

Neural Architectures

Top Venues

Tiny Papers @ ICLR

Publications

Arnav Chavan, Nahush Lele, Deepak K. Gupta
Surgical Feature-Space Decomposition of LLMs: Why, When and How? ACL (1) (2024)
Arnav Chavan, Nahush Lele, Deepak Gupta
Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models. Tiny Papers @ ICLR (2024)
Akash Guna R. T., Arnav Chavan, Deepak Gupta
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. Tiny Papers @ ICLR (2024)
Akash Guna R. T., Arnav Chavan, Deepak Gupta
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. CoRR (2024)
Arnav Chavan, Nahush Lele, Deepak Gupta
Surgical Feature-Space Decomposition of LLMs: Why, When and How? CoRR (2024)
Arnav Chavan, Raghav Magazine, Shubham Kushwaha, Mérouane Debbah, Deepak Gupta
Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward. CoRR (2024)
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)
Rishabh Tiwari, Arnav Chavan, Deepak 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)
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)
Arnav Chavan, Nahush Lele, Deepak K. Gupta
Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models. CoRR (2023)
Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR (2023)
Deepak K. Gupta, Gowreesh Mago, Arnav Chavan, Dilip K. Prasad
Patch Gradient Descent: Training Neural Networks on Very Large Images. CoRR (2023)
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)
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 (2022)
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 (2022)
Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning. CoRR (2022)
Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning. CVPR (2022)
Oliver Rippel, Arnav Chavan, Chucai Lei, Dorit Merhof
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations. IMPROVE (2022)
Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta
Rescaling CNN through Learnable Repetition of Network Parameters. CoRR (2021)
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations. CoRR (2021)
Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta
Rescaling CNN Through Learnable Repetition of Network Parameters. ICIP (2021)
Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta
ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations. ICLR (2021)
Oliver Rippel, Arnav Chavan, Chucai Lei, Dorit Merhof
Transfer Learning Gaussian Anomaly Detection by Fine-Tuning Representations. CoRR (2021)
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 (2021)
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 (2020)
Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj
Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection. CoRR (2020)
Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj
Multi-plateau Ensemble For Endoscopic Artefact Segmentation And Detection. EndoCV@ISBI (2020)