3 papers
cs.CV2025
Dynamic VLM-Guided Negative Prompting for Diffusion Models
Hoyeon Chang, Seungjin Kim, Yoonseok Choi
We propose a novel approach for dynamic negative prompting in diffusion models that leverages Vision-Language Models (VLMs) to adaptively generate negative prompts during the denoi…
cs.CL2025
Latent Reasoning via Sentence Embedding Prediction
Hyeonbin Hwang, Byeongguk Jeon, Seungone Kim +7
Autoregressive language models (LMs) generate one token at a time, yet human reasoning operates over higher-level abstractions - sentences, propositions, and concepts. This contras…
cs.CL2024
How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
Seongyun Lee, Geewook Kim, Jiyeon Kim +4
Vision-Language adaptation (VL adaptation) transforms Large Language Models (LLMs) into Large Vision-Language Models (LVLMs) for multimodal tasks, but this process often compromise…