126 citations · 279 across the 40 of their papers we have counts for
13 papers · 1 filter
UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models
Sejoon Oh, Yiqiao Jin, Megha Sharma +4
Multimodal large language models (MLLMs) have revolutionized vision-language understanding but remain vulnerable to multimodal jailbreak attacks, where adversarial inputs are metic…
Do Large Language Models Align with Core Mental Health Counseling Competencies?
Viet Cuong Nguyen, Mohammad Taher, Dongwan Hong +8
The rapid evolution of Large Language Models (LLMs) presents a promising solution to the global shortage of mental health professionals. However, their alignment with essential cou…
MedHalu: Hallucinations in Responses to Healthcare Queries by Large Language Models
Vibhor Agarwal, Yiqiao Jin, Mohit Chandra +3
Large language models (LLMs) are starting to complement traditional information seeking mechanisms such as web search. LLM-powered chatbots like ChatGPT are gaining prominence amon…
Adversarial Text Rewriting for Text-aware Recommender Systems
Sejoon Oh, Gaurav Verma, Srijan Kumar
Text-aware recommender systems incorporate rich textual features, such as titles and descriptions, to generate item recommendations for users. The use of textual features helps mit…
A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speech
Gaurav Verma, Rynaa Grover, Jiawei Zhou +4
Violence-provoking speech -- speech that implicitly or explicitly promotes violence against the members of the targeted community, contributed to a massive surge in anti-Asian crim…
Supporters and Skeptics: LLM-based Analysis of Engagement with Mental Health (Mis)Information Content on Video-sharing Platforms
Viet Cuong Nguyen, Mini Jain, Abhijat Chauhan +7
Over one in five adults in the US lives with a mental illness. In the face of a shortage of mental health professionals and offline resources, online short-form video content has g…
Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories
Yiqiao Jin, Andrew Zhao, Yeon-Chang Lee +3
We developed DyGETViz, a novel framework for effectively visualizing dynamic graphs (DGs) that are ubiquitous across diverse real-world systems. This framework leverages recent adv…
SVD-AE: Simple Autoencoders for Collaborative Filtering
Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee +2
Collaborative filtering (CF) methods for recommendation systems have been extensively researched, ranging from matrix factorization and autoencoder-based to graph filtering-based m…
Corrective or Backfire: Characterizing and Predicting User Response to Social Correction
Bing He, Yingchen Ma, Mustaque Ahamad +1
Online misinformation poses a global risk with harmful implications for society. Ordinary social media users are known to actively reply to misinformation posts with counter-misinf…
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning
Sejoon Oh, Berk Ustun, Julian McAuley +1
Modern recommender systems may output considerably different recommendations due to small perturbations in the training data. Changes in the data from a single user will alter the…
Cross-Modal Projection in Multimodal LLMs Doesn't Really Project Visual Attributes to Textual Space
Gaurav Verma, Minje Choi, Kartik Sharma +3
Multimodal large language models (MLLMs) like LLaVA and GPT-4(V) enable general-purpose conversations about images with the language modality. As off-the-shelf MLLMs may have limit…
Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation
Neng Kai Nigel Neo, Yeon-Chang Lee, Yiqiao Jin +2
The Fair Graph Anomaly Detection (FairGAD) problem aims to accurately detect anomalous nodes in an input graph while avoiding biased predictions against individuals from sensitive…
MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms
Yiqiao Jin, Minje Choi, Gaurav Verma +2
Social media platforms are hubs for multimodal information exchange, encompassing text, images, and videos, making it challenging for machines to comprehend the information or emot…