Martin Foltin

According to our database, Martin Foltin authored at least 31 papers between 2002 and 2026.

Collaborative distances:

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

2026

Hard to See, Hard to Label: Generative and Symbolic Acquisition for Subtle Visual Phenomena.

Renjith Prasad, Rishabh Sharma, Andrew E. Shao, Ann Mary Justine Koomthanam, Shreyas Kulkarni, Suparna Bhattacharya, Martin Foltin, Amit P. Sheth, David Orozco, Matthew Quinn, Brian Sammuli

CoRR, April, 2026

CEBC: Conformal Evidence-Bounded Control for Low-Hallucination Vision-Language Generation.

Ashish Mishra, Tarun Kumar, Arpit Shah, Suparna Bhattacharya, Martin Foltin

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

InfrastructureSentinel: Policy Enforced Guardrails for Secure MCP-driven Infrastructure Agents.

Tarun Kumar, Aalap Tripathy, Gayathri Saranathan, Martin Foltin, Suparna Bhattacharya, Scott Hinchley, Donald M. Bahls, David Brookshire, Larry Kaplan, Robert W. Wisniewski

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Erasing CLIP Memories: Non-Destructive, Data-Free Zero-Shot class Unlearning in CLIP Models.

Ashish Mishra, Tarun Kumar, Gyanaranjan Nayak, Arpit Shah, Suparna Bhattacharya, Martin Foltin

CoRR, December, 2025

Selective, Controlled and Domain-Agnostic Unlearning in Pretrained CLIP: A Training- and Data-Free Approach.

Ashish Mishra, Gyanaranjan Nayak, Tarun Kumar, Arpit Shah, Suparna Bhattacharya, Martin Foltin

CoRR, December, 2025

The Data Fusion Labeler (dFL): Challenges and Solutions to Data Harmonization, Labeling, and Provenance in Fusion Energy.

Craig Michoski, Matthew Waller, Brian Sammuli, Zeyu Li, Tapan Ganatma Nakkina, Raffi Nazikian, Sterling Paul Smith, David Orozco, Dongyang Kuang, Martin Foltin, Erik Olofsson, Mike Fredrickson, Jerry Louis-Jeune, David R. Hatch, Todd A. Oliver, Mitchell Clark, Steph-Yves Louis

CoRR, November, 2025

Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction.

Atif Hassan, Tarun Kumar, Ashish Mishra, Sergey Serebryakov, Satish Kumar Mopur, Phanidhar Koganti, Murthy Chelankuri, Ramanagopal V. Vogety, Suparna Bhattacharya, Martin Foltin

CoRR, November, 2025

Framework for tracking metadata, lineage and model provenance in hybrid simulation-AI HPC exascale workflows.

Martin Foltin, Andrew E. Shao, Rishabh Sharma, Shreyas Kulkarni, Ann Mary Justine Koomthanam, Aalap Tripathy, Cong Xu, Wenqian Dong, Suparna Bhattacharya, Brian Sammuli, Paolo Faraboschi

Proceedings of the Cray User Group, 2025

SubLIME: Subset Selection via Rank Correlation Prediction for Data-Efficient LLM Evaluation.

Gayathri Saranathan, Cong Xu, Mahammad Parwez Alam, Tarun Kumar, Martin Foltin, Soon Yee Wong, Suparna Bhattacharya

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

2024

Common Metadata Framework: Integrated Framework for Trustworthy Artificial Intelligence Pipelines.

Ann Mary Justine Koomthanam, Aalap Tripathy, Sergey Serebryakov, Gyanaranjan Nayak, Martin Foltin, Suparna Bhattacharya

IEEE Internet Comput., 2024

Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization.

Revathy Venkataramanan, Aalap Tripathy, Tarun Kumar, Sergey Serebryakov, Annmary Justine, Arpit Shah, Suparna Bhattacharya, Martin Foltin, Paolo Faraboschi, Kaushik Roy, Amit P. Sheth

Frontiers Big Data, 2024

Data Efficient Evaluation of Large Language Models and Text-to-Image Models via Adaptive Sampling.

Cong Xu, Gayathri Saranathan, Mahammad Parwez Alam, Arpit Shah, James Lim, Soon Yee Wong, Martin Foltin, Suparna Bhattacharya

CoRR, 2024

LLM-Guided Counterfactual Data Generation for Fairer AI.

Ashish Mishra, Gyanaranjan Nayak, Suparna Bhattacharya, Tarun Kumar, Arpit Shah, Martin Foltin

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments.

Gayathri Saranathan, Ayana Ghosh, Martin Foltin, Ann Mary Justine Koomthanam, Aalap Tripathy, Maxim A. Ziatdinov, Suparna Bhattacharya, Kevin Roccapriore, Paolo Faraboschi

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

Towards FAIR Workflows for Federated Experimental Sciences.

Gayathri Saranathan, Martin Foltin, Aalap Tripathy, Annmary Justine, Maxim A. Ziatdinov, Ayana Ghosh, Kevin Roccapriore, Supama Bhattacharya, Paolo Faraboschi

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

2023

Knowledge Graph Empowered Machine Learning Pipelines for Improved Efficiency, Reusability, and Explainability.

Revathy Venkataramanan, Aalap Tripathy, Martin Foltin, Hong Yung Yip, Annmary Justine, Amit P. Sheth

IEEE Internet Comput., 2023

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs.

Giacomo Pedretti, John Moon, Pedro Bruel, Sergey Serebryakov, Ron M. Roth, Luca Buonanno, Tobias Ziegler, Cong Xu, Martin Foltin, Paolo Faraboschi, Jim Ignowski, Catherine E. Graves

CoRR, 2023

Workflows Community Summit 2022: A Roadmap Revolution.

Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala, Debbie Bard, Peer-Timo Bremer, Ian Buckley, Silvina Caíno-Lores, Kyle Chard, Carole A. Goble, Shantenu Jha, Daniel S. Katz, Daniel E. Laney, Manish Parashar, Frédéric Suter, Nick Tyler, Thomas D. Uram, Ilkay Altintas, Stefan Andersson, William Arndt, Juan Aznar, Jonathan Bader, Bartosz Balis, Chris Blanton, Kelly Rosa Braghetto, Aharon Brodutch, Paul Brunk, Henri Casanova, Alba Cervera-Lierta, Justin Chigu, Tainã Coleman, Nick Collier, Iacopo Colonnelli, Frederik Coppens, Michael R. Crusoe, Will Cunningham, Bruno de Paula Kinoshita, Paolo Di Tommaso, Charles M. Doutriaux, Matthew Downton, Wael R. Elwasif, Bjoern Enders, Chris Erdmann, Thomas Fahringer, Ludmilla Figueiredo, Rosa Filgueira, Martin Foltin, Anne Fouilloux, Luiz Gadelha, Andy Gallo, Artur García-Sáez, et al.

CoRR, 2023

Towards Rapid Autonomous Electron Microscopy with Active Meta-Learning.

Gayathri Saranathan, Martin Foltin, Aalap Tripathy, Maxim A. Ziatdinov, Ann Mary Justine Koomthanam, Suparna Bhattacharya, Ayana Ghosh, Kevin Roccapriore, Sreenivas Rangan Sukumar, Paolo Faraboschi

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Dataset Efficient Training with Model Ensembling.

Yeonju Ro, Cong Xu, Agnieszka Ciborowska, Suparna Bhattacharya, Frankie Li, Martin Foltin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Self-learning Data Foundation for Scientific AI.

Annmary Justine, Sergey Serebryakov, Cong Xu, Aalap Tripathy, Suparna Bhattacharya, Paolo Faraboschi, Martin Foltin

Proceedings of the Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 2022

2021

Tree-based machine learning performed in-memory with memristive analog CAM.

Giacomo Pedretti, Catherine E. Graves, Can Li, Sergey Serebryakov, Xia Sheng, Martin Foltin, Ruibin Mao, John Paul Strachan

CoRR, 2021

Data-Aware Storage Tiering for Deep Learning.

Cong Xu, Suparna Bhattacharya, Martin Foltin, Suren Byna, Paolo Faraboschi

Proceedings of the 6th IEEE/ACM International Parallel Data Systems Workshop, 2021

2020

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM.

Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei Hwu, Kaushik Roy

IEEE Trans. Computers, 2020

2019

FPGA Demonstrator of a Programmable Ultra-Efficient Memristor-Based Machine Learning Inference Accelerator.

Martin Foltin, Glaucimar Aguiar, Rodrigo Antunes, Plínio Silveira, Gustavo Knuppe, Joao Ambrosi, Soumitra Chatterjee, Jitendra Onkar Kolhe, Sunil Lakshiminarashimha, Dejan S. Milojicic, John Paul Strachan, Craig Warner, Amit Sharma, Eddie Lee, Sai Rahul Chalamalasetti, Chris Brueggen, Charles Williams, Nathaniel Jansen, Felipe Saenz, Luis Federico Li

Proceedings of the 2019 IEEE International Conference on Rebooting Computing, 2019

PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference.

Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-mei W. Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic

Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, 2019

2018

Regular Expression Matching with Memristor TCAMs for Network Security.

Catherine E. Graves, Wen Ma, Xia Sheng, Brent Buchanan, Le Zheng, Sity Lam, Xuema Li, Sai Rahul Chalamalasetti, Lennie Kiyama, Martin Foltin, John Paul Strachan, Matthew P. Hardy

Proceedings of the 14th IEEE/ACM International Symposium on Nanoscale Architectures, 2018

Regular Expression Matching with Memristor TCAMs.

Catherine E. Graves, Wen Ma, Xia Sheng, Brent Buchanan, Le Zheng, Sity Lam, Xuema Li, Sai Rahul Chalamalasetti, Lennie Kiyama, Martin Foltin, Matthew P. Hardy, John Paul Strachan

Proceedings of the 2018 IEEE International Conference on Rebooting Computing, 2018

Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning.

Joao Ambrosi, Aayush Ankit, Rodrigo Antunes, Sai Rahul Chalamalasetti, Soumitra Chatterjee, Izzat El Hajj, Guilherme Fachini, Paolo Faraboschi, Martin Foltin, Sitao Huang, Wen-Mei Hwu, Gustavo Knuppe, Sunil Vishwanathpur Lakshminarasimha, Dejan S. Milojicic, Mohan Parthasarathy, Filipe Ribeiro, Lucas Rosa, Kaushik Roy, Plínio Silveira, John Paul Strachan

Proceedings of the 2018 IEEE International Conference on Rebooting Computing, 2018

2002

Genetic Algorithm Based Adaptive Control Of An Electromechanical MIMO System.

Ivan Sekaj, Martin Foltin, Michal Gonos

Proceedings of the GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, 2002

Efficient stimulus independent timing abstraction model based on a new concept of circuit block transparency.

Martin Foltin, Brian Foutz, Sean Tyler

Proceedings of the 39th Design Automation Conference, 2002