most citedControlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning

2 citations · 5 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2024

Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-II: Intra-day and Experimental Validation

Rahul K. Gupta, Sherif Fahmy, Max Chevron +2

In Part-I, we presented an optimal day-ahead scheduling scheme for dispatching active distribution networks accounting for the flexibility provided by electric vehicle charging sta…

eess.SY2024

Grid-aware Scheduling and Control of Electric Vehicle Charging Stations for Dispatching Active Distribution Networks. Part-I: Day-ahead and Numerical Validation

Rahul K. Gupta, Sherif Fahmy, Max Chevron +3

This paper proposes a grid-aware scheduling and control framework for Electric Vehicle Charging Stations (EVCSs) for dispatching the operation of an active power distribution netwo…

eess.SY20242 cited

Analysis of Fairness-promoting Optimization Schemes of Photovoltaic Curtailments for Voltage Regulation in Power Distribution Networks

Rahul K. Gupta, Daniel K. Molzahn

Active power curtailment of photovoltaic (PV) generation is commonly exercised to mitigate over-voltage issues in power distribution networks. However, fairness concerns arise as c…

eess.SY2024

Fairness-aware Photovoltaic Generation Limits for Voltage Regulation in Power Distribution Networks using Conservative Linear Approximations

Rahul K. Gupta, Paprapee Buason, Daniel K. Molzahn

This paper proposes a framework for fairly curtailing photovoltaic (PV) plants in response to the over-voltage problem in PV-rich distribution networks. The framework imposes PV ge…

cs.CL20232 cited

Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning

Mustafa Safa Ozdayi, Charith Peris, Jack FitzGerald +5

Large Language Models (LLMs) are known to memorize significant portions of their training data. Parts of this memorized content have been shown to be extractable by simply querying…

eess.SY20231 cited

Experimental Validation of Model-less Robust Voltage Control using Measurement-based Estimated Voltage Sensitivity Coefficients

Rahul Gupta, Mario Paolone

Increasing adoption of smart meters and phasor measurement units (PMUs) in power distribution networks are enabling the adoption of data-driven/model-less control schemes to mitiga…