Seshu Tirupathi

Orcid: 0000-0003-2998-0826

According to our database1, Seshu Tirupathi authored at least 36 papers between 2017 and 2026.

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Timeline

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Bibliography

2026
TRACES: Tagging Reasoning Steps for Adaptive Cost-Efficient Early-Stopping.
CoRR, April, 2026

Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models.
CoRR, April, 2026

Bridging the High-Frequency Data Gap: A Millisecond-Resolution Network Dataset for Advancing Time Series Foundation Models.
CoRR, March, 2026

Shapelets-Enriched Selective Forecasting using Time Series Foundation Models.
CoRR, January, 2026

Risk Atlas Nexus: A System for Managing AI Risks.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Step-Tagging: Toward controlling the generation of Language Reasoning Models through step monitoring.
CoRR, December, 2025

Dynamic Features Adaptation in Networking: Toward Flexible training and Explainable inference.
CoRR, October, 2025

Interpreting LLM-as-a-Judge Policies via Verifiable Global Explanations.
CoRR, October, 2025

Pre-Hoc Predictions in AutoML: Leveraging LLMs to Enhance Model Selection and Benchmarking for Tabular datasets.
CoRR, October, 2025

GAF-Guard: An Agentic Framework for Risk Management and Governance in Large Language Models.
CoRR, July, 2025

Power Utilization in Open RAN: Key Findings From a USA Testbed.
IEEE Commun. Lett., June, 2025

AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources.
CoRR, March, 2025

AT4TS : Autotune for Time Series Foundation Models.
Trans. Mach. Learn. Res., 2025

The Time-Energy Model: Selective Time-Series Forecasting Using Energy-Based Models.
Trans. Mach. Learn. Res., 2025

Intent Based Machine Learning for Networks Using Large Language Models.
Proceedings of the IEEE Conference on Network Function Virtualization and Software-Defined Networking, 2025


Selective-HeatFlex: Selective Forecasting of Heat Pump Flexibility using Model Confidence.
Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, 2025

FiTEM: Fine-Tuning Time-Series Foundation Models for Selective Forecasting.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2025

Usage Governance Advisor: From Intent to AI Governance.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Usage Governance Advisor: from Intent to AI Governance.
CoRR, 2024

Decentralized Multi-Party Multi-Network AI for Global Deployment of 6G Wireless Systems.
CoRR, 2024

Domain Adaptation for Time series Transformers using One-step fine-tuning.
CoRR, 2024

Online Learning and Model Pruning Against Concept Drifts in Edge Devices.
Proceedings of the 10th IEEE International Conference on Network Softwarization, 2024

2023

2022
GOFLEX: extracting, aggregating and trading flexibility based on FlexOffers for 500+ prosumers in 3 European cities [operational systems paper].
Proceedings of the e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022, 2022

Prequential Model Selection for Time Series Forecasting based on Saliency Maps.
Proceedings of the IEEE International Conference on Big Data, 2022


Distributed Incremental Machine Learning for Big Time Series Data.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Aggregation of nonlinearly enhanced experts with application to electricity load forecasting.
Appl. Soft Comput., 2021

Practical Perfusion Quantification in Multispectral Endoscopic Video: Using the Minutes after ICG Administration to Assess Tissue Pathology.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020
Scalable Deployment of AI Time-series Models for IoT.
CoRR, 2020

Perfusion Quantification from Endoscopic Videos: Learning to Read Tumor Signatures.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
AI Modelling and Time-series Forecasting Systems for Trading Energy Flexibility in Distribution Grids.
Proceedings of the Tenth ACM International Conference on Future Energy Systems, 2019

2018
Castor: Contextual IoT Time Series Data and Model Management at Scale.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2017
Power systems data fusion based on belief propagation.
Proceedings of the 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, 2017


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