6 papers · 1 filter
Text-Guided Multi-Scale Frequency Representation Adaptation
Weicai Yan, Xinhua Ma, Wang Lin +1
Parameter-efficient fine-tuning methods introduce a small number of training parameters, enabling pre-trained models to adapt rapidly to new data distributions. While these methods…
Proact-VL: A Proactive VideoLLM for Real-Time AI Companions
Weicai Yan, Yuhong Dai, Qi Ran +6
Proactive and real-time interactive experiences are essential for human-like AI companions, yet face three key challenges: (1) achieving low-latency inference under continuous stre…
Decoupling Stability and Plasticity for Multi-Modal Test-Time Adaptation
Yongbo He, Zirun Guo, Tao Jin
Adapting pretrained multi-modal models to evolving test-time distributions, known as multi-modal test-time adaptation, presents a significant challenge. Existing methods frequently…
Thinking with Programming Vision: Towards a Unified View for Thinking with Images
Zirun Guo, Minjie Hong, Feng Zhang +2
Multimodal large language models (MLLMs) that think with images can interactively use tools to reason about visual inputs, but current approaches often rely on a narrow set of tool…
Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision
Weicai Yan, Wang Lin, Zirun Guo +5
Prompt learning has demonstrated promising results in fine-tuning pre-trained multimodal models. However, the performance improvement is limited when applied to more complex and fi…
ConceptGuard: Continual Personalized Text-to-Image Generation with Forgetting and Confusion Mitigation
Zirun Guo, Tao Jin
Diffusion customization methods have achieved impressive results with only a minimal number of user-provided images. However, existing approaches customize concepts collectively, w…