11 citations · 23 across the 6 of their papers we have counts for
9 papers
Quantifying Social Biases Using Templates is Unreliable
Preethi Seshadri, Pouya Pezeshkpour, Sameer Singh
Recently, there has been an increase in efforts to understand how large language models (LLMs) propagate and amplify social biases. Several works have utilized templates for fairne…
The Extremal GDoF Gain of Optimal versus Binary Power Control in User Interference Networks Is
Yao-Chia Chan, Pouya Pezeshkpour, Chunhua Geng +1
Using ideas from Generalized Degrees of Freedom (GDoF) analyses and extremal network theory, this work studies the extremal gain of optimal power control over binary (on/off) power…
An Empirical Comparison of Instance Attribution Methods for NLP
Pouya Pezeshkpour, Sarthak Jain, Byron C. Wallace +1
Widespread adoption of deep models has motivated a pressing need for approaches to interpret network outputs and to facilitate model debugging. Instance attribution methods constit…
ParsiNLU: A Suite of Language Understanding Challenges for Persian
Daniel Khashabi, Arman Cohan, Siamak Shakeri +22
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich l…
Generating User-friendly Explanations for Loan Denials using GANs
Ramya Srinivasan, Ajay Chander, Pouya Pezeshkpour
Financial decisions impact our lives, and thus everyone from the regulator to the consumer is interested in fair, sound, and explainable decisions. There is increasing competitive…
Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications
Pouya Pezeshkpour, Yifan Tian, Sameer Singh
Representing entities and relations in an embedding space is a well-studied approach for machine learning on relational data. Existing approaches, however, primarily focus on impro…