172 citations · 610 across the 14 of their papers we have counts for
16 papers
Beyond the Sycophancy Score: How Task, Model, and Pressure Shape LLM Yielding
Guang Yang, Homa Hosseinmardi, Fengchen Liu +1
Large language models (LLMs) often abandon a correct answer, or endorse a user's position, once the user pushes back. This behavior, called sycophancy, is usually reported as a sin…
How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment
Guang Yang, Fengchen Liu, Alex Wang +2
State-aligned distortion has been documented in China-origin text-based large language models (LLMs), but whether, and in what form, it arises in multimodal systems has not been sy…
How You Ask Shapes What You Get: Auditing Breast-Cancer Misinformation in TikTok Search
Pooriya Jamie, Homa Hosseinmardi, Rezvaneh Rezapour +3
Millions of people use TikTok to seek health information, yet little is known about how users' search queries shape exposure to health misinformation. Whereas prior algorithm audit…
Beyond Binary Detection: A Multi-Dimensional Taxonomy of Cancer Misinformation on Reddit
Aria Pessianzadeh, Pooriya Jamie, Naima Sultana +6
Cancer-related discussions on social media provide important spaces for information exchange and peer support, but can also expose users to misinformation with implications for pre…
LLM-Assisted Reranking to Operationalize Nuanced Objectives in Recommender Systems
Amir Ghasemian, Homa Hosseinmardi, Upasana Dutta +1
Recommender systems have grown from content-organization tools into sophisticated systems that shape daily behavior. By controlling what we see, they shape what we perceive, raisin…
Asking Back: Interaction-Layer Antidistillation Watermarks
Guang Yang, Amir Ghasemian, Fengchen Liu +3
Detecting unauthorized knowledge distillation from a deployed LLM API is hard because the defender controls neither the attacker's training pipeline nor the next-token logits. Exis…
Asymmetric Phase Coding Audio Watermarking
Guang Yang, Amir Ghasemian, Ninareh Mehrabi +1
The proliferation of deepfake audio challenges voice-based authentication systems; passive forensic detectors are sensitive to evolving generative models and to real-world channel…
Seeking Help, Facing Harm: Auditing TikTok's Mental Health Recommendations
Pooriya Jamie, Amir Ghasemian, Homa Hosseinmardi
Recommender systems on social media increasingly mediate how users encounter mental health content, yet it remains unclear whether they distinguish help-seeking from distress expre…
Link Prediction Accuracy on Real-World Networks Under Non-Uniform Missing Edge Patterns
Xie He, Amir Ghasemian, Eun Lee +3
Real-world network datasets are typically obtained in ways that fail to capture all edges. The patterns of missing data are often non-uniform as they reflect biases and other short…
Causally estimating the effect of YouTube's recommender system using counterfactual bots
Homa Hosseinmardi, Amir Ghasemian, Miguel Rivera-Lanas +3
In recent years, critics of online platforms have raised concerns about the ability of recommendation algorithms to amplify problematic content, with potentially radicalizing conse…
The Enmity Paradox
Amir Ghasemian, Nicholas A. Christakis
The "friendship paradox" of social networks states that, on average, "your friends have more friends than you do." Here, we theoretically and empirically explore a related and over…
Examining the consumption of radical content on YouTube
Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset +3
Although it is under-studied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world. Recently, Y…
Stacking Models for Nearly Optimal Link Prediction in Complex Networks
Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan +2
Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speedup the collection of network data and impro…
Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction
Homa Hosseinmardi, Amir Ghasemian, Shrikanth Narayanan +2
Today's densely instrumented world offers tremendous opportunities for continuous acquisition and analysis of multimodal sensor data providing temporal characterization of an indiv…
Evaluating Overfit and Underfit in Models of Network Community Structure
Amir Ghasemian, Homa Hosseinmardi, Aaron Clauset
A common data mining task on networks is community detection, which seeks an unsupervised decomposition of a network into structural groups based on statistical regularities in the…
Detectability thresholds and optimal algorithms for community structure in dynamic networks
Amir Ghasemian, Pan Zhang, Aaron Clauset +2
We study the fundamental limits on learning latent community structure in dynamic networks. Specifically, we study dynamic stochastic block models where nodes change their communit…