Search Results for author:
Found 6 papers, 2 papers with code
HiddenDetect: Detecting Jailbreak Attacks against Large Vision-Language Models via Monitoring Hidden States
The integration of additional modalities increases the susceptibility of large vision-language models (LVLMs) to safety risks, such as jailbreak attacks, compared to their language-only counterparts.
Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models
Fine-tuning large language models (LLMs) based on human preferences, commonly achieved through reinforcement learning from human feedback (RLHF), has been effective in improving their performance.
DebiasDiff: Debiasing Text-to-image Diffusion Models with Self-discovering Latent Attribute Directions
Then, the distribution indicator is multiplied by the set of adapters to guide the generation process towards the prescribed distribution.
RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting
While Multimodal Large Language Models (MLLMs) have made remarkable progress in vision-language reasoning, they are also more susceptible to producing harmful content compared to models that focus solely on text.
Event-Customized Image Generation
To extend customized image generation to more complex scenes for general real-world applications, we propose a new task: event-customized image generation.
Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation
In this paper, we aim to adapt a generic pretrained model with a relatively small amount of domain-specific data.
Ranked #42 on
Time Series Forecasting
on ETTh1 (336) Multivariate
