1 citations · 1 across the 6 of their papers we have counts for
6 papers
Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation
Hongbo Jiang, Jie Li, Yunhang Shen +2
Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, their strong performance often m…
Can Unified Generation and Understanding Models Maintain Semantic Equivalence Across Different Output Modalities?
Hongbo Jiang, Jie Li, Yunhang Shen +4
Unified Multimodal Large Language Models (U-MLLMs) integrate understanding and generation within a single architecture. However, existing evaluations typically assess these capabil…
Unleashing MLLMs on the Edge: A Unified Framework for Cross-Modal ReID via Adaptive SVD Distillation
Hongbo Jiang, Jie Li, Xinqi Cai +4
Practical cloud-edge deployment of Cross-Modal Re-identification (CM-ReID) faces challenges due to maintaining a fragmented ecosystem of specialized cloud models for diverse modali…
KORE: Enhancing Knowledge Injection for Large Multimodal Models via Knowledge-Oriented Controls
Kailin Jiang, Hongbo Jiang, Ning Jiang +7
Large Multimodal Models encode extensive factual knowledge in their pre-trained weights. However, its knowledge remains static and limited, unable to keep pace with real-world deve…
Insert Anything: Image Insertion via In-Context Editing in DiT
Wensong Song, Hong Jiang, Zongxing Yang +2
This work presents Insert Anything, a unified framework for reference-based image insertion that seamlessly integrates objects from reference images into target scenes under flexib…
ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning
Huandong Chang, Zicheng Ma, Mingyuan Ma +4
Low-Rank Adaptation (LoRA) has become a widely adopted technique for fine-tuning large-scale pre-trained models with minimal parameter updates. However, existing methods rely on fi…