Arnav Das

Orcid: 0000-0003-3083-6389

Affiliations:
  • University of Washington, Seattle, WA, USA
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA (former)


According to our database1, Arnav Das authored at least 14 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2025
Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective.
Trans. Mach. Learn. Res., 2025

PRimuS: Pretraining IMU Encoders with Multimodal Self-Supervision.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Learning.
CoRR, 2024

How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold.
CoRR, 2024

Deep Submodular Peripteral Networks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

An End-to-End Submodular Framework for Data-Efficient In-Context Learning.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Prompting Foundational Models for Omni-supervised Instance Segmentation.
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.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Accelerating Batch Active Learning Using Continual Learning Techniques.
Trans. Mach. Learn. Res., 2023

Effective Backdoor Mitigation Depends on the Pre-training Objective.
CoRR, 2023

RadarHD: Demonstrating Lidar-like Point Clouds from mmWave Radar.
Proceedings of the 29th Annual International Conference on Mobile Computing and Networking, 2023

High Resolution Point Clouds from mmWave Radar.
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.
CoRR, 2020


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