Colin Samplawski

Researcher in machine learning.

Publications

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
40th AAAI Conference on Artificial Intelligence (AAAI 2026)
Singapore
aaai

2025

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
Workshop on Preventing Unauthorized Knowledge Use from Large Language Models
Conference on Neural Information Processing Systems (NeurIPS 2025)
San Diego, CA
openreview workshop
A Preliminary Study into the Conceptual Design of Aircraft using Simulation-Based Inference
Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam Cobb
Workshop on Machine Learning and the Physical Sciences
Conference on Neural Information Processing Systems (NeurIPS 2025)
San Diego, CA
openreview neurips
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
41st Conference on Uncertainty in Artificial Intelligence (UAI 2025)
Rio de Janeiro, Brazil
acm
End-to-End Differentiable Multi-View Tracking: Architecture and Fine-Tuning Experiments
Colin Samplawski, Shiwei Fang, Benjamin M. Marlin
28th International Conference on Information Fusion (FUSION 2025)
Rio de Janeiro, Brazil
ieee

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 Michael Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha
Workshop on Safe Generative AI
Conference on Neural Information Processing Systems (NeurIPS 2024)
Vancouver, Canada
openreview workshop
FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors
Jason Wu, Ziqi Wang, Xiaomin Ouyang, Ho Lyun Jeong, Colin Samplawski, Lance M. Kaplan, Benjamin Marlin, Mani Srivastava
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)
Abu Dhabi, UAE
ieee code
Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
Hui Wei, Maxwell A. Xu, Colin Samplawski, James M. Rehg, Santosh Kumar, Benjamin M. Marlin
Conference on Health, Inference, and Learning (CHIL 2024)
New York, NY
arxiv pmc

2023

IoBT-MAX: A Multimodal Analytics eXperimentation Testbed for IoBT Research
Benjamin M. Marlin, Niranjan Suri, Shiwei Fang, Mani B. Srivastava, Colin Samplawski, Ziqi Wang, Maggie Wigness
IEEE Military Communications Conference (MILCOM 2023)
Boston, MA
ieee
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
Colin Samplawski, Shiwei Fang, Ziqi Wang, Deepak Ganesan, Mani Srivastava, Benjamin M. Marlin
39th Conference on Uncertainty in Artificial Intelligence (UAI 2023)
Pittsburgh, PA
pdf pmlr openreview

2022

Uncertainty Quantification Using Query-Based Object Detectors
Meet P. Vadera, Colin Samplawski, Benjamin M. Marlin
Workshop on Uncertainty Quantification for Computer Vision
17th European Conference on Computer Vision (ECCV 2022)
Tel Aviv, Israel
workshop

2021

Optimizing Intelligent Edge-clouds with Partitioning, Compression and Speculative Inference
Shiwei Fang, Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin Marlin, Tarek Abdelzaher, Maggie B. Wigness
IEEE Military Communications Conference (MILCOM 2021)
San Diego, CA
ieee
Towards Transformer-Based Real-Time Object Detection at the Edge: A Benchmarking Study
Colin Samplawski, Benjamin M. Marlin
IEEE Military Communications Conference (MILCOM 2021)
San Diego, CA
ieee
Towards an Accurate Latency Model for Convolutional Neural Network Layers on GPUs
Jinyang Li, Runyu Ma, Vikram Sharma Mailthody, Colin Samplawski, Benjamin Marlin, Songqing Chen, Shuochao Yao, Tarek Abdelzaher
IEEE Military Communications Conference (MILCOM 2021)
San Diego, CA
ieee

2020

Towards Object Detection Under IoT Resource Constraints: Combining Partitioning, Slicing and Compression
Colin Samplawski, Jin Huang, Deepak Ganesan, Benjamin M. Marlin
2nd International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things
18th ACM Conference on Embedded Networked Sensor Systems (SenSys 2020)
Virtual Event, Japan
acm
CLIO: Enabling Automatic Compilation of Deep Learning Pipelines Across IoT and Cloud
Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin M. Marlin, Heesung Kwon
26th Annual International Conference on Mobile Computing and Networking (MobiCom 2020)
London, United Kingdom
acm
Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels
Colin Samplawski, Erik Learned-Miller, Heesung Kwon, Benjamin M. Marlin
Workshop on Visual Learning with Limited Labels
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020)
Virtual Event
pdf workshop
Learning Graph-Based Priors for Generalized Zero-Shot Learning
Colin Samplawski, Jannik Wolff, Tassilo Klein, Moin Nabi
1st International Workshop on Deep Learning on Graphs: Methodologies and Applications
34th AAAI Conference on Artificial Intelligence (AAAI 2020)
New York, NY
arxiv patent

2019

Weakly Supervised Content and Style Disentanglement with Gaussian Mixture VAEs
Jan Nikolas Morshuis, Colin Samplawski, Moin Nabi
Workshop on Information Theory and Machine Learning
Conference on Neural Information Processing Systems (NeurIPS 2019)
Vancouver, Canada
pdf workshop