14 citations · 21 across the 20 of their papers we have counts for
9 papers · 1 filter
ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behavior
Weikai Lu, Ziqian Zeng, Kehua Zhang +5
Multimodal Large Language Models (MLLMs) are increasingly vulnerable to multimodal Indirect Prompt Injection (IPI) attacks, which embed malicious instructions in images, videos, or…
ProCache: Constraint-Aware Feature Caching with Selective Computation for Diffusion Transformer Acceleration
Fanpu Cao, Yaofo Chen, Zeng You +1
Diffusion Transformers (DiTs) have achieved state-of-the-art performance in generative modeling, yet their high computational cost hinders real-time deployment. While feature cachi…
RCP-Merging: Merging Long Chain-of-Thought Models with Domain-Specific Models by Considering Reasoning Capability as Prior
Junyao Yang, Jianwei Wang, Huiping Zhuang +2
Large Language Models (LLMs) with long chain-of-thought (CoT) capability, termed Reasoning Models, demonstrate superior intricate problem-solving abilities through multi-step long…
Decompose, Plan in Parallel, and Merge: A Novel Paradigm for Large Language Models based Planning with Multiple Constraints
Zhengdong Lu, Weikai Lu, Yiling Tao +6
Despite significant advances in Large Language Models (LLMs), planning tasks still present challenges for LLM-based agents. Existing planning methods face two key limitations: heav…
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Xiang Zhang, Run He, Jiao Chen +5
Class-incremental learning (CIL) enables models to learn new classes continually without forgetting previously acquired knowledge. Multi-label CIL (MLCIL) extends CIL to a real-wor…
Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning
Run He, Di Fang, Yicheng Xu +5
Exemplar-Free Class-Incremental Learning (EFCIL) aims to sequentially learn from distinct categories without retaining exemplars but easily suffers from catastrophic forgetting of…
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
Jianwei Wang, Chengming Shi, Junyao Yang +5
The success of large language models (LLMs) has attracted many individuals to fine-tune them for domain-specific tasks by uploading their data. However, in sensitive areas like hea…
SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings
Weikai Lu, Hao Peng, Huiping Zhuang +2
Multimodal Large Language Models (MLLMs) have serious security vulnerabilities.While safety alignment using multimodal datasets consisting of text and data of additional modalities…
X-SGS: Safe and Generalizable Gaussian Splatting with X-dimensional Watermarks
Zihang Cheng, Wentao Bao, Huiping Zhuang +6
3D Gaussian Splatting (3DGS) has been widely used in 3D reconstruction and 3D generation. However, the rapid adoption of 3D Gaussian Splatting raises growing concerns about informa…