4 citations · 9 across the 9 of their papers we have counts for
10 papers
RADAR: Rubric-Aware Dependency and Redundancy Analysis for LLM-as-Judge Evaluation
Divyansh Singh, Reza Davari, Afra Mashhadi
Rubric-based LLM-as-judge pipelines often assume that evaluation criteria provide independent signals. In practice, however, criteria can be behaviorally coupled: improving one cri…
Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)
Yifan Liu, Jaime Arguello, Orland Hoeber +30
This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI\&AS), which examined how GenAI is reshaping academic search systems and research practices.…
ToxiTwitch: Toward Emote-Aware Hybrid Moderation for Live Streaming Platforms
Baktash Ansari, Elias Martin, Afra Mashhadi
The rapid growth of live-streaming platforms such as Twitch has introduced complex challenges in moderating toxic behavior. Traditional moderation approaches, such as human annotat…
Remembering Unequally: Global and Disciplinary Bias in LLM Reconstruction of Scholarly Coauthor Lists
Ghazal Kalhor, Afra Mashhadi
Ongoing breakthroughs in large language models (LLMs) are reshaping scholarly search and discovery interfaces. While these systems offer new possibilities for navigating scientific…
Comparing Fairness of Generative Mobility Models
Daniel Wang, Jack McFarland, Afra Mashhadi +1
This work examines the fairness of generative mobility models, addressing the often overlooked dimension of equity in model performance across geographic regions. Predictive models…
Phoenix: A Federated Generative Diffusion Model
Fiona Victoria Stanley Jothiraj, Afra Mashhadi
Generative AI has made impressive strides in enabling users to create diverse and realistic visual content such as images, videos, and audio. However, training generative models on…
Survey of Federated Learning Models for Spatial-Temporal Mobility Applications
Yacine Belal, Sonia Ben Mokhtar, Hamed Haddadi +2
Federated learning involves training statistical models over edge devices such as mobile phones such that the training data is kept local. Federated Learning (FL) can serve as an i…
Personalized Emotion Detection using IoT and Machine Learning
Fiona Victoria Stanley Jothiraj, Afra Mashhadi
The Medical Internet of Things, a recent technological advancement in medicine, is incredibly helpful in providing real-time monitoring of health metrics. This paper presents a non…
Caring Without Sharing: A Federated Learning Crowdsensing Framework for Diversifying Representation of Cities
Michael Cho, Afra Mashhadi
Mobile Crowdsensing has become main stream paradigm for researchers to collect behavioral data from citizens in large scales. This valuable data can be leveraged to create centrali…
Fairness in Federated Learning for Spatial-Temporal Applications
Afra Mashhadi, Alex Kyllo, Reza M. Parizi
Federated learning involves training statistical models over remote devices such as mobile phones while keeping data localized. Training in heterogeneous and potentially massive ne…