3 papers
cs.CR2026
Jailbreaking Frontier Foundation Models Through Intention Deception
Xinhe Wang, Katia Sycara, Yaqi Xie
Large (vision-)language models exhibit remarkable capability but remain highly susceptible to jailbreaking. Existing safety training approaches aim to have the model learn a refusa…
cs.CL2026
Your Reasoning Benchmark May Not Test Reasoning: Revealing Perception Bottleneck in Abstract Reasoning Benchmarks
Xinhe Wang, Jin Huang, Xingjian Zhang +2
Reasoning benchmarks such as the Abstraction and Reasoning Corpus (ARC) and ARC-AGI are widely used to assess progress in artificial intelligence and are often interpreted as probe…
cs.LG2025
Adversarial Attacks on Data Attribution
Xinhe Wang, Pingbang Hu, Junwei Deng +1
Data attribution aims to quantify the contribution of individual training data points to the outputs of an AI model, which has been used to measure the value of training data and c…