4 citations · 12 across the 10 of their papers we have counts for
11 papers
IcFuzz: Fuzzing Isaac Sim with Semantic Stage Guidance and Multi-level Mutation
Zhixiang Chen, Zhuangbin Chen, Ruoxi Jia +4
Robotics simulators serve as a foundational infrastructure for embodied AI, facilitating safe and scalable robotic system development. NVIDIA Isaac Sim has emerged as one of the mo…
Beyond Similarity: Trustworthy Memory Search for Personal AI Agents
Jiawen Zhang, Kejia Chen, Jiachen Ma +7
Personal AI agents increasingly rely on long-term memory to provide persistent personalization across sessions. However, existing memory pipelines are largely driven by semantic si…
Mitigating Many-shot Jailbreak Attacks with One Single Demonstration
Kejia Chen, Jiawen Zhang, Boheng Li +6
Many-shot jailbreaking (MSJ) causes safety-aligned language models to answer harmful queries by preceding them with many harmful question-answer demonstrations. We study why this a…
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety
Xingjun Ma, Yifeng Gao, Yixu Wang +45
The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…
MLAN: Language-Based Instruction Tuning Preserves and Transfers Knowledge in Multimodal Language Models
Jianhong Tu, Zhuohao Ni, Nicholas Crispino +8
We present a novel visual instruction tuning strategy to improve the zero-shot task generalization of multimodal large language models by building a firm text-only knowledge base.…
AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies
Yi Zeng, Yu Yang, Andy Zhou +9
Foundation models (FMs) provide societal benefits but also amplify risks. Governments, companies, and researchers have proposed regulatory frameworks, acceptable use policies, and…
AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies
Yi Zeng, Kevin Klyman, Andy Zhou +6
We present a comprehensive AI risk taxonomy derived from eight government policies from the European Union, United States, and China and 16 company policies worldwide, making a sig…
BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models
Yi Zeng, Weiyu Sun, Tran Ngoc Huynh +3
Safety backdoor attacks in large language models (LLMs) enable the stealthy triggering of unsafe behaviors while evading detection during normal interactions. The high dimensionali…
Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A Pilot Study
Chenguang Wang, Ruoxi Jia, Xin Liu +1
Pre-training image representations from the raw text about images enables zero-shot vision transfer to downstream tasks. Through pre-training on millions of samples collected from…
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
Zhuowen Yuan, Zidi Xiong, Yi Zeng +4
Recent advancements in Large Language Models (LLMs) have showcased remarkable capabilities across various tasks in different domains. However, the emergence of biases and the poten…
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
Ruoxi Jia, David Dao, Boxin Wang +6
Given a data set containing millions of data points and a data consumer who is willing to pay for $ to train a machine learning (ML) model over , how…