Arnav Das

According to our database, Arnav Das authored at least 17 papers between 2020 and 2026.

Collaborative distances:

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

2026

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions.

Jeff A. Bilmes, Gantavya Bhatt, Arnav M. Das

CoRR, May, 2026

2025

How Many Images Does It Take? Estimating Imitation Thresholds in Text-to-Image Models.

Sahil Verma, Royi Rassin, Arnav Mohanty Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff A. Bilmes, Hannaneh Hajishirzi, Yanai Elazar

Trans. Mach. Learn. Res., 2025

Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective.

Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P. Dickerson, Pin-Yu Chen, Jeff A. Bilmes

Trans. Mach. Learn. Res., 2025

PRimuS: Pretraining IMU Encoders with Multimodal Self-Supervision.

Arnav M. Das, Chi Ian Tang, Fahim Kawsar, Mohammad Malekzadeh

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation.

Arnav M. Das, Gantavya Bhatt, Lilly Kumari, Sahil Verma, Jeff A. Bilmes

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning.

Jifan Zhang, Yifang Chen, Gregory Canal, Arnav Mohanty Das, Gantavya Bhatt, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon Shaolei Du, Kevin Jamieson, Robert D. Nowak

J. Data-centric Mach. Learn. Res., 2024

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Learning.

Arnav Mohanty Das, Gantavya Bhatt, Lilly Kumari, Sahil Verma, Jeff A. Bilmes

CoRR, 2024

How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold.

Sahil Verma, Royi Rassin, Arnav Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff A. Bilmes, Hannaneh Hajishirzi, Yanai Elazar

CoRR, 2024

Deep Submodular Peripteral Networks.

Gantavya Bhatt, Arnav Das, Jeff A. Bilmes

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

An End-to-End Submodular Framework for Data-Efficient In-Context Learning.

Lilly Kumari, Shengjie Wang, Arnav Das, Tianyi Zhou, Jeff A. Bilmes

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Prompting Foundational Models for Omni-supervised Instance Segmentation.

Arnav M. Das, Ritwick Chaudhry, Kaustav Kundu, Davide Modolo

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.

Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash, Robert D. Nowak

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Accelerating Batch Active Learning Using Continual Learning Techniques.

Arnav Mohanty Das, Gantavya Bhatt, Megh Manoj Bhalerao, Vianne R. Gao, Rui Yang, Jeff A. Bilmes

Trans. Mach. Learn. Res., 2023

Effective Backdoor Mitigation Depends on the Pre-training Objective.

Sahil Verma, Gantavya Bhatt, Avi Schwarzschild, Soumye Singhal, Arnav Mohanty Das, Chirag Shah, John P. Dickerson, Jeff A. Bilmes

CoRR, 2023

RadarHD: Demonstrating Lidar-like Point Clouds from mmWave Radar.

Akarsh Prabhakara, Tao Jin, Arnav Das, Gantavya Bhatt, Lilly Kumari, Elahe Soltanaghai, Jeff A. Bilmes, Swarun Kumar, Anthony Rowe

Proceedings of the 29th Annual International Conference on Mobile Computing and Networking, 2023

High Resolution Point Clouds from mmWave Radar.

Akarsh Prabhakara, Tao Jin, Arnav Das, Gantavya Bhatt, Lilly Kumari, Elahe Soltanaghai, Jeff A. Bilmes, Swarun Kumar, Anthony Rowe

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2020

Physics-inspired deep learning to characterize the signal manifold of quasi-circular, spinning, non-precessing binary black hole mergers.

Asad Khan, Eliu A. Huerta, Arnav Das

CoRR, 2020