Preethi Seshadri

According to our database, Preethi Seshadri authored at least 14 papers between 2016 and 2026.

Collaborative distances:

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

2026

Where Do Images Come From? Analyzing Captions to Geographically Profile Datasets.

Abhipsa Basu, Yugam Bahl, Kirti Bhagat, Preethi Seshadri, R. Venkatesh Babu, Danish Pruthi

CoRR, February, 2026

Lost in Simulation: LLM-Simulated Users are Unreliable Proxies for Human Users in Agentic Evaluations.

Preethi Seshadri, Samuel Cahyawijaya, Ayomide Odumakinde, Sameer Singh, Seraphina Goldfarb-Tarrant

CoRR, January, 2026

2025

Agree to Disagree? A Meta-Evaluation of LLM Misgendering.

Arjun Subramonian, Vagrant Gautam, Preethi Seshadri, Dietrich Klakow, Kai-Wei Chang, Yizhou Sun

CoRR, April, 2025

Who Does the Giant Number Pile Like Best: Analyzing Fairness in Hiring Contexts.

Preethi Seshadri, Seraphina Goldfarb-Tarrant

CoRR, January, 2025

How Many Images Does It Take? Estimating Imitation Thresholds in Text-to-Image Models.

Sahil Verma, Royi Rassin, Arnav Mohanty Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff A. Bilmes, Hannaneh Hajishirzi, Yanai Elazar

Trans. Mach. Learn. Res., 2025

Learning Robust Representations for Communications over Interference-Limited Channels.

Shubham Paul, Sudharsan Senthil, Preethi Seshadri, Nambi Seshadri, Ravinder David Koilpillai

Proceedings of the 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025

Small Changes, Large Consequences: Analyzing the Allocational Fairness of LLMs in Hiring Contexts.

Preethi Seshadri, Hongyu Chen, Sameer Singh, Seraphina Goldfarb-Tarrant

Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025

2024

How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold.

Sahil Verma, Royi Rassin, Arnav Das, Gantavya Bhatt, Preethi Seshadri, Chirag Shah, Jeff A. Bilmes, Hannaneh Hajishirzi, Yanai Elazar

CoRR, 2024

The Bias Amplification Paradox in Text-to-Image Generation.

Preethi Seshadri, Sameer Singh, Yanai Elazar

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Are Models Biased on Text without Gender-related Language?

Catarina G. Belém, Preethi Seshadri, Yasaman Razeghi, Sameer Singh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022

Quantifying Social Biases Using Templates is Unreliable.

Preethi Seshadri, Pouya Pezeshkpour, Sameer Singh

CoRR, 2022

2019

Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification.

Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap, Mihail Douhaniaris, Preethi Seshadri, John Whaley

CoRR, 2019

A Seed-Augment-Train Framework for Universal Digit Classification.

Vinay Uday Prabhu, Sanghyun Han, Dian Ang Yap, Mihail Douhaniaris, Preethi Seshadri

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2016

MyCS at 5: Assessing a Middle-years CS Curriculum.

Brenda Castro, Terrence Diaz, Marissa Gee, Rebekah Justice, David Kwan, Preethi Seshadri, Zachary Dodds

Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 2016