Mansi Sakarvadia

According to our database, Mansi Sakarvadia authored at least 9 papers between 2023 and 2024.

Collaborative distances:

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

2024

De Bello Homomorphico: Investigation of the extensibility of the OpenFHE library with basic mathematical functions by means of common approaches using the example of the CKKS cryptosystem.

Thomas Prantl, Lukas Horn, Simon Engel, Lukas Iffländer, Lukas Beierlieb, Christian Krupitzer, André Bauer, Mansi Sakarvadia, Ian T. Foster, Samuel Kounev

Int. J. Inf. Sec., April, 2024

Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning.

Sahil Sethi, Sai Reddy, Mansi Sakarvadia, Jordan Serotte, Darlington Nwaudo, Nicholas Maassen, Lewis Shi

CoRR, 2024

Towards Interpreting Language Models: A Case Study in Multi-Hop Reasoning.

Mansi Sakarvadia

CoRR, 2024

SoK: On Finding Common Ground in Loss Landscapes Using Deep Model Merging Techniques.

Arham Khan, Todd Nief, Nathaniel Hudson, Mansi Sakarvadia, Daniel Grzenda, Aswathy Ajith, Jordan Pettyjohn, Kyle Chard, Ian T. Foster

CoRR, 2024

Mitigating Memorization In Language Models.

Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Nathaniel Hudson, Caleb Geniesse, Kyle Chard, Yaoqing Yang, Ian T. Foster, Michael W. Mahoney

CoRR, 2024

2023

Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism.

Mansi Sakarvadia, Arham Khan, Aswathy Ajith, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster

CoRR, 2023

Lazy Python Dependency Management in Large-Scale Systems.

Alok Kamatar, Mansi Sakarvadia, Valérie Hayot-Sasson, Kyle Chard, Ian T. Foster

Proceedings of the 19th IEEE International Conference on e-Science, 2023

Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models.

Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster

Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, 2023

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision.

Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster

Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, 2023