Chaitanya Devaguptapu

According to our database, Chaitanya Devaguptapu authored at least 15 papers between 2019 and 2025.

Collaborative distances:

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

2025

Finding Needles in Images: Can Multimodal LLMs Locate Fine Details?

Parth Thakkar, Ankush Agarwal, Prasad Kasu, Pulkit Bansal, Chaitanya Devaguptapu

CoRR, August, 2025

Towards a Training Free Approach for 3D Scene Editing.

Vivek Madhavaram, Shivangana Rawat, Chaitanya Devaguptapu, Charu Sharma, Manohar Kaul

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

Hybrid Graphs for Table-and-Text based Question Answering using LLMs.

Ankush Agarwal, Chaitanya Devaguptapu, Ganesh S

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Finding Needles in Images: Can Multi-modal LLMs Locate Fine Details?

Parth Thakkar, Ankush Agarwal, Prasad Kasu, Pulkit Bansal, Chaitanya Devaguptapu

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Semantic Graph Consistency: Going Beyond Patches for Regularizing Self-Supervised Vision Transformers.

Chaitanya Devaguptapu, Sumukh Aithal, Shrinivas Ramasubramanian, Moyuru Yamada, Manohar Kaul

CoRR, 2024

Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation.

Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu, V. S. S. V. Prasad, Charu Sharma, Manohar Kaul

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

HOLMES: Hyper-Relational Knowledge Graphs for Multi-hop Question Answering using LLMs.

Pranoy Panda, Ankush Agarwal, Chaitanya Devaguptapu, Manohar Kaul, A. P. Prathosh

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

2023

Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation.

Siddharth Katageri, Arkadipta De, Chaitanya Devaguptapu, VSSV Prasad, Charu Sharma, Manohar Kaul

CoRR, 2023

Δ-Networks for Efficient Model Patching.

Chaitanya Devaguptapu, Samarth Sinha, K. J. Joseph, Vineeth N. Balasubramanian, Animesh Garg

CoRR, 2023

2022

Learning Modular Structures That Generalize Out-of-Distribution.

Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian

CoRR, 2022

Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract).

Arjun Ashok, Chaitanya Devaguptapu, Vineeth N. Balasubramanian

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

On Adversarial Robustness: A Neural Architecture Search perspective.

Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Pulkit Gopalani, Vineeth N. Balasubramanian

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2020

An Empirical Study on the Robustness of NAS based Architectures.

Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal, Vineeth N. Balasubramanian

CoRR, 2020

On Initial Pools for Deep Active Learning.

Akshay L. Chandra, Sai Vikas Desai, Chaitanya Devaguptapu, Vineeth N. Balasubramanian

Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

2019

Borrow From Anywhere: Pseudo Multi-Modal Object Detection in Thermal Imagery.

Chaitanya Devaguptapu, Ninad Akolekar, Manuj M. Sharma, Vineeth N. Balasubramanian

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019