6 papers
Auditing Machine Unlearning: A Systematic Research on Whether Models Truly Forget
Dayong Ye, Tianqing Zhu, Ruiding Huang +5
Machine unlearning has been extensively studied in response to growing privacy concerns and regulatory requirements. However, auditing whether unlearning algorithms have truly eras…
StableI2I: Spotting Unintended Changes in Image-to-Image Transition
Jiayang Li, Shuo Cao, Xiaohui Li +6
In most real-world image-to-image (I2I) scenarios, existing evaluations primarily focus on instruction following and the perceptual quality or aesthetics of the generated images. H…
Accelerating Masked Image Generation by Learning Latent Controlled Dynamics
Kaiwen Zhu, Quansheng Zeng, Yuandong Pu +8
Masked Image Generation Models (MIGMs) have achieved great success, yet their efficiency is hampered by the multiple steps of bi-directional attention. In fact, there exists notabl…
UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture
Shuo Cao, Jiayang Li, Xiaohui Li +12
Multimodal large language models (MLLMs) have achieved remarkable progress in visual understanding tasks such as visual grounding, segmentation, and captioning. However, their abil…
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Shuo Cao, Nan Ma, Jiayang Li +12
The rapid advancement of educational applications, artistic creation, and AI-generated content (AIGC) technologies has substantially increased practical requirements for comprehens…
WanJuanSiLu: A High-Quality Open-Source Webtext Dataset for Low-Resource Languages
Jia Yu, Fei Yuan, Rui Min +20
This paper introduces the open-source dataset WanJuanSiLu, designed to provide high-quality training corpora for low-resource languages, thereby advancing the research and developm…