4 papers
Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs
Yang Dai, Jianxiang An, Tianwei Lin +6
Multimodal Large Language Models (MLLMs) have achieved success across various domains. However, their applicability tends to degrade when confronted with different types of data in…
AIMeter: Measuring, Analyzing, and Visualizing Energy and Carbon Footprint of AI Workloads
Hongzhen Huang, Kunming Zhang, Hanlong Liao +2
The rapid advancement of AI, particularly large language models (LLMs), has raised significant concerns about the energy use and carbon emissions associated with model training and…
AlignLLaVA: Cascaded Human and Large Language Model Preference Alignment for Multi-modal Instruction Curation
Hongzhe Huang, Jiang Liu, Zhewen Yu +8
Recent advances in Multi-modal Large Language Models (MLLMs), such as LLaVA-series models, are driven by massive machine-generated instruction-following data tuning. Such automatic…
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…