Arnav Chavan

According to our database, Arnav Chavan authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward.

Arnav Chavan, Raghav Magazine, Shubham Kushwaha, Mérouane Debbah, Deepak K. Gupta

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures.

Akash Guna R. T., Arnav Chavan, Deepak K. Gupta

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models.

Arnav Chavan, Nahush Lele, Deepak K. Gupta

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Surgical Feature-Space Decomposition of LLMs: Why, When and How?

Arnav Chavan, Nahush Lele, Deepak K. Gupta

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning.

Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen

CoRR, 2023

Patch Gradient Descent: Training Neural Networks on Very Large Images.

Deepak K. Gupta, Gowreesh Mago, Arnav Chavan, Dilip K. Prasad

CoRR, 2023

RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning.

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On Designing Light-Weight Object Trackers Through Network Pruning: Use CNNS or Transformers?

Saksham Aggarwal, Taneesh Gupta, Pawan Kumar Sahu, Arnav Chavan, Rishabh Tiwari, Dilip K. Prasad, Deepak K. Gupta

Proceedings of the IEEE International Conference on Acoustics, 2023

A Comparative Study on the Impact of Model Compression Techniques on Fairness in Language Models.

Krithika Ramesh, Arnav Chavan, Shrey Pandit, Sunayana Sitaram

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations.

Oliver Rippel, Arnav Chavan, Chucai Lei, Dorit Merhof

Proceedings of the 2nd International Conference on Image Processing and Vision Engineering, 2022

Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning.

Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space.

Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.

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

Medical Image Anal., 2021

ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations.

Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta

Proceedings of the 9th International Conference on Learning Representations, 2021

Rescaling CNN Through Learnable Repetition of Network Parameters.

Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

A translational pathway of deep learning methods in GastroIntestinal Endoscopy.

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

CoRR, 2020

Multi-plateau Ensemble For Endoscopic Artefact Segmentation And Detection.

Suyog Jadhav, Udbhav Bamba, Arnav Chavan, Rishabh Tiwari, Aryan Raj

Proceedings of the 2nd International Workshop and Challenge on Computer Vision in Endoscopy, 2020