4 citations · 7 across the 7 of their papers we have counts for
7 papers
PolicyGuide: From Guarding One Action to Guiding the Whole Workflow for Policy-Compliant LLM Agents
Seongjae Kang, Taehyung Yu, Sung Ju Hwang
Customer-service LLM agents must follow organizational policy when acting on a user's behalf. Compliance failures arise from either forbidden actions, such as granting an ineligibl…
PolicyGuard: A Dialogue-Grounded Sub-Agent Verifier for Policy Adherence in LLM Agents
Seongjae Kang, Taehyung Yu, Sung Ju Hwang
LLM agents handle user requests on behalf of organizations through tool calls and must follow the company policies stated in their system prompts. Prior work approaches this as a s…
T-MAP: Red-Teaming LLM Agents with Trajectory-aware Evolutionary Search
Hyomin Lee, Sangwoo Park, Yumin Choi +3
While prior red-teaming efforts have focused on eliciting harmful text outputs from large language models (LLMs), such approaches fail to capture agent-specific vulnerabilities tha…
Enhancing Variational Autoencoders with Smooth Robust Latent Encoding
Hyomin Lee, Minseon Kim, Sangwon Jang +2
Variational Autoencoders (VAEs) have played a key role in scaling up diffusion-based generative models, as in Stable Diffusion, yet questions regarding their robustness remain larg…
Optimizing Query Generation for Enhanced Document Retrieval in RAG
Hamin Koo, Minseon Kim, Sung Ju Hwang
Large Language Models (LLMs) excel in various language tasks but they often generate incorrect information, a phenomenon known as "hallucinations". Retrieval-Augmented Generation (…
Automatic Jailbreaking of the Text-to-Image Generative AI Systems
Minseon Kim, Hyomin Lee, Boqing Gong +2
Recent AI systems have shown extremely powerful performance, even surpassing human performance, on various tasks such as information retrieval, language generation, and image gener…
Context-dependent Instruction Tuning for Dialogue Response Generation
Jin Myung Kwak, Minseon Kim, Sung Ju Hwang
Recent language models have achieved impressive performance in natural language tasks by incorporating instructions with task input during fine-tuning. Since all samples in the sam…