6 papers
Bounded-Compute Multimodal Regression for Product-Rating Prediction
William Leach, Ru He, Sizhuo Ma +4
Vision-language models (VLMs) are increasingly attractive for multimodal quality assessment, but their default reliance on autoregressive text generation and dynamic visual process…
LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation
Jinze Li, Xiaoyan Yang, Shuo Yang +5
Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization methods typically retrieve or su…
Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models
Chen Zheng, Yuxuan Lai, Haoyang Lu +3
The handwriting of Chinese characters is a fundamental aspect of learning the Chinese language. Previous automated assessment methods often framed scoring as a regression problem.…
Do Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMs
Yutong Song, Jiang Wu, Shaofan Yuan +5
Personalized large language models are often expected to follow explicit style instructions, yet we find that such instructions can undermine the user-specific characteristics that…
CARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generation
Yutong Song, Jiang Wu, Weijia Zhang +7
Adapting large language models to individual users remains challenging due to the tension between fine-grained personalization and scalable deployment. We present CARD, a hierarchi…
Towards Better Optimization For Listwise Preference in Diffusion Models
Jiamu Bai, Xin Yu, Meilong Xu +6
Reinforcement learning from human feedback (RLHF) has proven effectiveness for aligning text-to-image (T2I) diffusion models with human preferences. Although Direct Preference Opti…