6 papers
World-To-Image: Grounding Text-to-Image Generation with Agent-Driven World Knowledge
Moo Hyun Son, Jintaek Oh, Sun Bin Mun +2
While text-to-image (T2I) models can synthesize high-quality images, their performance degrades significantly when prompted with novel or out-of-distribution (OOD) entities due to…
Throttling Web Agents Using Reasoning Gates
Abhinav Kumar, Jaechul Roh, Ali Naseh +2
AI web agents use Internet resources at far greater speed, scale, and complexity -- changing how users and services interact. Deployed maliciously or erroneously, these agents coul…
R1dacted: Investigating Local Censorship in DeepSeek's R1 Language Model
Ali Naseh, Harsh Chaudhari, Jaechul Roh +3
DeepSeek recently released R1, a high-performing large language model (LLM) optimized for reasoning tasks. Despite its efficient training pipeline, R1 achieves competitive performa…
Multilingual and Multi-Accent Jailbreaking of Audio LLMs
Jaechul Roh, Virat Shejwalkar, Amir Houmansadr
Large Audio Language Models (LALMs) have significantly advanced audio understanding but introduce critical security risks, particularly through audio jailbreaks. While prior work h…
OverThink: Slowdown Attacks on Reasoning LLMs
Abhinav Kumar, Jaechul Roh, Ali Naseh +4
Most flagship language models generate explicit reasoning chains, enabling inference-time scaling. However, producing these reasoning chains increases token usage (i.e., reasoning…
FameBias: Embedding Manipulation Bias Attack in Text-to-Image Models
Jaechul Roh, Andrew Yuan, Jinsong Mao
Text-to-Image (T2I) diffusion models have rapidly advanced, enabling the generation of high-quality images that align closely with textual descriptions. However, this progress has…