Manoj Acharya

According to our database, Manoj Acharya authored at least 21 papers between 2005 and 2026.

Collaborative distances:

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

2026

Breaking Bad: Interpretability-Based Safety Audits of State-of-the-Art LLMs.

Krishiv Agarwal, Ramneet Kaur, Colin Samplawski, Manoj Acharya, Anirban Roy, Daniel Elenius, Brian Matejek, Adam D. Cobb, Susmit Jha

CoRR, April, 2026

From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents.

Trilok Padhi, Ramneet Kaur, Krishiv Agarwal, Adam D. Cobb, Daniel Elenius, Manoj Acharya, Colin Samplawski, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha, Anirban Roy

CoRR, April, 2026

Do Diffusion Models Dream of Electric Planes? Discrete and Continuous Simulation-Based Inference for Aircraft Design.

Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb

CoRR, March, 2026

Trojans in Artificial Intelligence (TrojAI) Final Report.

Kristopher W. Reese, Taylor Kulp-McDowall, Michael Majurski, Timothy Blattner, Derek Juba, Peter Bajcsy, Antonio Cardone, Philippe Dessauw, Alden Dima, Anthony J. Kearsley, Melinda Kleczynski, Joel Vasanth, Walid Keyrouz, Chace Ashcraft, Neil Fendley, Ted Staley, Trevor Stout, Josh Carney, Greg Canal, William Redman, Aurora Schmidt, Cameron Hickert, William Paul, Jared Markowitz, Nathan Drenkow, David Shriver, Marissa Connor, Keltin Grimes, Marco Christiani, Hayden Moore, Jordan Widjaja, Kasimir Gabert, Uma Balakrishnan, Satyanadh Gundimada, John Jacobellis, Sandya Lakkur, Vitus Leung, Jon Roose, Casey Battaglino, Farinaz Koushanfar, Greg Fields, Xihe Gu, Yaman Jandali, Xinqiao Zhang, Tara Javidi, Akash Vartak, Tim Oates, Ben Erichson, Michael Mahoney, Rauf Izmailov, Xiangyu Zhang, Guangyu Shen, Siyuan Cheng, Shiqing Ma, XiaoFeng Wang, Haixu Tang, Di Tang, Xiaoyi Chen, Zihao Wang, Rui Zhu, Susmit Jha, Xiao Lin, Manoj Acharya, Weichao Zhou, Feisi Fu, Panagiota Kiourti, Chenyu Wang, Zijian Guo, H. M. Sabbir Ahmad, Wenchao Li, Chao Chen

CoRR, February, 2026

Privacy Preserving In-Context-Learning Framework for Large Language Models.

Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Privacy-Aware In-Context Learning for Large Language Models.

Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha

CoRR, September, 2025

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding.

Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya, Anirban Roy, Colin Samplawski, Brian Matejek, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha

CoRR, May, 2025

TeleLoRA: Teleporting Model-Specific Alignment Across LLMs.

Xiao Lin, Manoj Acharya, Anirban Roy, Susmit Jha

CoRR, March, 2025

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference.

Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Revisiting Multi-Modal LLM Evaluation.

Jian Lu, Shikhar Srivastava, Junyu Chen, Robik Shrestha, Manoj Acharya, Kushal Kafle, Christopher Kanan

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

2024

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI.

Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M. Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha

CoRR, 2024

2023

Generative AI in the Construction Industry: Opportunities & Challenges.

Prashnna Ghimire, Kyungki Kim, Manoj Acharya

CoRR, 2023

2022

Detecting out-of-context objects using contextual cues.

Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran

CoRR, 2022

Detecting Out-Of-Context Objects Using Graph Contextual Reasoning Network.

Manoj Acharya, Anirban Roy, Kaushik Koneripalli, Susmit Jha, Christopher Kanan, Ajay Divakaran

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

2nd Place Solution for SODA10M Challenge 2021 - Continual Detection Track.

Manoj Acharya, Christopher Kanan

CoRR, 2021

2020

REMIND Your Neural Network to Prevent Catastrophic Forgetting.

Tyler L. Hayes, Kushal Kafle, Robik Shrestha, Manoj Acharya, Christopher Kanan

Proceedings of the Computer Vision - ECCV 2020, 2020

RODEO: Replay for Online Object Detection.

Manoj Acharya, Tyler L. Hayes, Christopher Kanan

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

VQD: Visual Query Detection In Natural Scenes.

Manoj Acharya, Karan Jariwala, Christopher Kanan

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

RITnet: Real-time Semantic Segmentation of the Eye for Gaze Tracking.

Aayush K. Chaudhary, Rakshit Sunil Kothari, Manoj Acharya, Shusil Dangi, Nitinraj Nair, Reynold Bailey, Christopher Kanan, Gabriel J. Diaz, Jeff B. Pelz

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

TallyQA: Answering Complex Counting Questions.

Manoj Acharya, Kushal Kafle, Christopher Kanan

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2005

SOA in the Real World - Experiences.

Manoj Acharya, Abhijit Kulkarni, Rajesh Kuppili, Rohit Mani, Nitin More, Srinivasa Narayanan, Parthiv Patel, Kenneth W. Schuelke, Subbu N. Subramanian

Proceedings of the Service-Oriented Computing, 2005