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ORCIDMartin Foltin
- > Home > Persons > Martin Foltin
Publications
- 2025
[c16]Gayathri Saranathan, Cong Xu, Mahammad Parwez Alam, Tarun Kumar, Martin Foltin, Soon Yee Wong, Suparna Bhattacharya:
SubLIME: Subset Selection via Rank Correlation Prediction for Data-Efficient LLM Evaluation. ACL (1) 2025: 30572-30593- [c15]Martin Foltin, Andrew Shao, Rishabh Sharma
, Shreyas Kulkarni, Ann Mary Justine Koomthanam, Aalap Tripathy, Cong Xu, Wenqian Dong, Suparna Bhattacharya, Brian Sammuli, Paolo Faraboschi:
Framework for tracking metadata, lineage and model provenance in hybrid simulation-AI HPC exascale workflows. CUG 2025: 147-155 - [i10]Atif Hassan, Tarun Kumar, Ashish Mishra, Sergey Serebryakov, Satish Kumar Mopur, Phanidhar Koganti, Murthy Chelankuri, Ramanagopal V. Vogety, Suparna Bhattacharya, Martin Foltin:
Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction. CoRR abs/2511.03149 (2025) - [i8]Ashish Mishra, Gyanaranjan Nayak, Tarun Kumar, Arpit Shah, Suparna Bhattacharya, Martin Foltin:
Selective, Controlled and Domain-Agnostic Unlearning in Pretrained CLIP: A Training- and Data-Free Approach. CoRR abs/2512.14113 (2025) - [i7]Ashish Mishra, Tarun Kumar, Gyanaranjan Nayak, Arpit Shah, Suparna Bhattacharya, Martin Foltin:
Erasing CLIP Memories: Non-Destructive, Data-Free Zero-Shot class Unlearning in CLIP Models. CoRR abs/2512.14137 (2025) - 2024
- [j4]Revathy Venkataramanan, Aalap Tripathy, Tarun Kumar, Sergey Serebryakov, Annmary Justine, Arpit Shah, Suparna Bhattacharya, Martin Foltin, Paolo Faraboschi, Kaushik Roy, Amit P. Sheth:
Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization. Frontiers Big Data 7 (2024) - [j3]Ann Mary Justine Koomthanam, Aalap Tripathy, Sergey Serebryakov, Gyanaranjan Nayak, Martin Foltin, Suparna Bhattacharya:
Common Metadata Framework: Integrated Framework for Trustworthy Artificial Intelligence Pipelines. IEEE Internet Comput. 28(3): 37-44 (2024) - [c13]Gayathri Saranathan, Ayana Ghosh, Martin Foltin, Ann Mary Justine Koomthanam, Aalap Tripathy, Maxim A. Ziatdinov, Suparna Bhattacharya, Kevin Roccapriore, Paolo Faraboschi:
Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments. SC Workshops 2024: 2154-2161 - [c12]Ashish Mishra, Gyanaranjan Nayak, Suparna Bhattacharya, Tarun Kumar, Arpit Shah, Martin Foltin:
LLM-Guided Counterfactual Data Generation for Fairer AI. WWW (Companion Volume) 2024: 1538-1545 - [i6]Cong Xu, Gayathri Saranathan, Mahammad Parwez Alam, Arpit Shah, James Lim, Soon Yee Wong, Martin Foltin, Suparna Bhattacharya:
Data Efficient Evaluation of Large Language Models and Text-to-Image Models via Adaptive Sampling. CoRR abs/2406.15527 (2024) - 2023
- [c11]Yeonju Ro, Cong Xu, Agnieszka Ciborowska, Suparna Bhattacharya, Frankie Li, Martin Foltin:
Dataset Efficient Training with Model Ensembling. CVPR Workshops 2023: 4700-4704 - [c10]Gayathri Saranathan, Martin Foltin, Aalap Tripathy, Maxim A. Ziatdinov, Ann Mary Justine Koomthanam, Suparna Bhattacharya, Ayana Ghosh, Kevin Roccapriore, Sreenivas Rangan Sukumar, Paolo Faraboschi:
Towards Rapid Autonomous Electron Microscopy with Active Meta-Learning. SC Workshops 2023: 81-87 - 2022
- [c9]Annmary Justine, Sergey Serebryakov, Cong Xu, Aalap Tripathy, Suparna Bhattacharya, Paolo Faraboschi, Martin Foltin:
Self-learning Data Foundation for Scientific AI. SMC 2022: 20-37 - 2021
- [c8]Cong Xu, Suparna Bhattacharya, Martin Foltin, Suren Byna, Paolo Faraboschi:
Data-Aware Storage Tiering for Deep Learning. PDSW@SC 2021: 23-28
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