| 2024 | ACL | Surgical Feature-Space Decomposition of LLMs: Why, When and How? | Arnav Chavan, Nahush Lele, Deepak K. Gupta |
| 2024 | ICLR | Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models. | Arnav Chavan, Nahush Lele, Deepak K. Gupta |
| 2024 | ICLR | Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. | Akash Guna R. T., Arnav Chavan, Deepak K. Gupta |
| 2024 | IJCAI | Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward. | Arnav Chavan, Raghav Magazine, Shubham Kushwaha, Mrouane Debbah, Deepak K. Gupta |
| 2023 | ACL | A Comparative Study on the Impact of Model Compression Techniques on Fairness in Language Models. | Krithika Ramesh, Arnav Chavan, Shrey Pandit, Sunayana Sitaram |
| 2023 | ICASSP | 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 |
| 2022 | CVPR | Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. | Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing |
| 2022 | CVPR | Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learning. | Arnav Chavan, Rishabh Tiwari, Udbhav Bamba, Deepak K. Gupta |
| 2021 | ICIP | Rescaling CNN Through Learnable Repetition of Network Parameters. | Arnav Chavan, Udbhav Bamba, Rishabh Tiwari, Deepak K. Gupta |
| 2021 | ICLR | ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations. | Rishabh Tiwari, Udbhav Bamba, Arnav Chavan, Deepak K. Gupta |