7 papers
Bridging Distribution Shift and AI Safety: Conceptual and Methodological Synergies
Chenruo Liu, Kenan Tang, Yao Qin +1
This paper bridges distribution shift and AI safety through a comprehensive analysis of their conceptual and methodological synergies. While prior discussions often focus on narrow…
ExpressEdit: Fast Editing of Stylized Facial Expressions with Diffusion Models in Photoshop
Kenan Tang, Jiasheng Guo, Jeffrey Lin +1
Facial expressions of characters are a vital component of visual storytelling. While current AI image editing models hold promise for assisting artists in the task of stylized expr…
Banana100: Breaking NR-IQA Metrics by 100 Iterative Image Replications with Nano Banana Pro
Kenan Tang, Praveen Arunshankar, Andong Hua +2
The multi-step, iterative image editing capabilities of multi-modal agentic systems have transformed digital content creation. Although latest image editing models faithfully follo…
SPICE: A Synergistic, Precise, Iterative, and Customizable Image Editing Workflow
Kenan Tang, Yanhong Li, Yao Qin
Prompt-based models have demonstrated impressive prompt-following capability at image editing tasks. However, the models still struggle with following detailed editing prompts or p…
Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs
Andong Hua, Kenan Tang, Chenhe Gu +3
Prompt sensitivity, referring to the phenomenon where paraphrasing (i.e., repeating something written or spoken using different words) leads to significant changes in large languag…
DIY-MKG: An LLM-Based Polyglot Language Learning System
Kenan Tang, Yanhong Li, Yao Qin
Existing language learning tools, even those powered by Large Language Models (LLMs), often lack support for polyglot learners to build linguistic connections across vocabularies i…