7 citations · 7 across the 5 of their papers we have counts for
6 papers
WEAVE: Unleashing and Benchmarking the In-context Interleaved Comprehension and Generation
Wei Chow, Jiachun Pan, Yongyuan Liang +10
Recent advances in unified multimodal models (UMMs) have enabled impressive progress in visual comprehension and generation. However, existing datasets and benchmarks focus primari…
Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs
Zhaoyu Fan, Kaihang Pan, Mingze Zhou +7
Knowledge editing enables multimodal large language models (MLLMs) to efficiently update outdated or incorrect information. However, existing benchmarks primarily emphasize cogniti…
DreamActor-H1: High-Fidelity Human-Product Demonstration Video Generation via Motion-designed Diffusion Transformers
Lizhen Wang, Zhurong Xia, Tianshu Hu +6
In e-commerce and digital marketing, generating high-fidelity human-product demonstration videos is important for effective product presentation. However, most existing frameworks…
ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding
Santosh Rajagopalan, Jonathan Vronsky, Songbai Yan +3
We present ALF (Advertiser Large Foundation model), a multi-modal transformer architecture for understanding advertiser behavior and intent across text, image, video, and structure…
WorldGPT: Empowering LLM as Multimodal World Model
Zhiqi Ge, Hongzhe Huang, Mingze Zhou +4
World models are progressively being employed across diverse fields, extending from basic environment simulation to complex scenario construction. However, existing models are main…
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks
Haoyi Duan, Yan Xia, Mingze Zhou +3
In recent years, the deployment of large-scale pre-trained models in audio-visual downstream tasks has yielded remarkable outcomes. However, these models, primarily trained on sing…