5 papers
Is Meta-Learning Out? Rethinking Unsupervised Few-Shot Classification with Limited Entropy
Yunchuan Guan, Yu Liu, Ke Zhou +4
Meta-learning is a powerful paradigm for tackling few-shot tasks. However, recent studies indicate that models trained with the whole-class training strategy can achieve comparable…
POEM: Precise Object-level Editing via MLLM control
Marco Schouten, Mehmet Onurcan Kaya, Serge Belongie +1
Diffusion models have significantly improved text-to-image generation, producing high-quality, realistic images from textual descriptions. Beyond generation, object-level image edi…
Gradient Imbalance in Direct Preference Optimization
Qinwei Ma, Jingzhe Shi, Can Jin +3
Direct Preference Optimization (DPO) has been proposed as a promising alternative to Proximal Policy Optimization (PPO) based Reinforcement Learning with Human Feedback (RLHF). How…
ChatMotion: A Multimodal Multi-Agent for Human Motion Analysis
Lei Li, Sen Jia, Jianhao Wang +4
Advancements in Multimodal Large Language Models (MLLMs) have improved human motion understanding. However, these models remain constrained by their "instruct-only" nature, lacking…
Bayesian Optimization for Controlled Image Editing via LLMs
Chengkun Cai, Haoliang Liu, Xu Zhao +6
In the rapidly evolving field of image generation, achieving precise control over generated content and maintaining semantic consistency remain significant limitations, particularl…