87 citations · 104 across the 37 of their papers we have counts for
9 papers · 1 filter
Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models
Mingyang Lyu, Yinqian Sun, Erliang Lin +4
Vision-Language-Action (VLA) models such as OpenVLA, Octo, and have shown strong generalization by leveraging large-scale demonstrations, yet their performance is still funda…
Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense
Guobin Shen, Dongcheng Zhao, Haibo Tong +3
Ensuring Large Language Model (LLM) safety remains challenging due to the absence of universal standards and reliable content validators, making it difficult to obtain effective tr…
Bidirectional Intention Inference Enhances LLMs' Defense Against Multi-Turn Jailbreak Attacks
Haibo Tong, Dongcheng Zhao, Guobin Shen +4
The remarkable capabilities of Large Language Models (LLMs) have raised significant safety concerns, particularly regarding "jailbreak" attacks that exploit adversarial prompts to…
DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values
Yao Liang, Dongcheng Zhao, Feifei Zhao +4
Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often overlook cultural and demographic vari…
Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
Bing Han, Feifei Zhao, Dongcheng Zhao +4
While fine-tuning services drive the rapid expansion of task capabilities in large language models (LLMs), they are often accompanied by the degradation and reorganization of safet…
C-VARC: A Large-Scale Chinese Value Rule Corpus for Value Alignment of Large Language Models
Ping Wu, Guobin Shen, Dongcheng Zhao +6
Aligning LLMs with Chinese values requires culturally grounded resources that connect abstract values to concrete behavioral guidance. We introduce C-VARC, a Chinese Value Rule Cor…
Continual Learning of Multiple Cognitive Functions with Brain-inspired Temporal Development Mechanism
Bing Han, Feifei Zhao, Yinqian Sun +2
Cognitive functions in current artificial intelligence networks are tied to the exponential increase in network scale, whereas the human brain can continuously learn hundreds of co…
Spiking World Model with Multi-Compartment Neurons for Model-based Reinforcement Learning
Yinqian Sun, Feifei Zhao, Mingyang Lv +1
Brain-inspired spiking neural networks (SNNs) have garnered significant research attention in algorithm design and perception applications. However, their potential in the decision…
Autonomous Alignment with Human Value on Altruism through Considerate Self-imagination and Theory of Mind
Haibo Tong, Enmeng Lu, Yinqian Sun +4
With the widespread application of Artificial Intelligence (AI) in human society, enabling AI to autonomously align with human values has become a pressing issue to ensure its sust…