3 papers
cs.SE2026
CoRE: A Fine-Grained Code Reasoning Benchmark Beyond Output Prediction
Jun Gao, Yun Peng, Qian Qiao +6
Despite strong performance on code generation tasks, it remains unclear whether large language models (LLMs) genuinely reason about code execution. Existing code reasoning benchmar…
cs.CV2026
Making MLLMs Blind: Adversarial Smuggling Attacks in MLLM Content Moderation
Zhiheng Li, Zongyang Ma, Yuntong Pan +8
Multimodal Large Language Models (MLLMs) are increasingly being deployed as automated content moderators. Within this landscape, we uncover a critical threat: Adversarial Smuggling…
cs.AI2026
Xuanwu: Evolving General Multimodal Models into an Industrial-Grade Foundation for Content Ecosystems
Zhiqian Zhang, Xu Zhao, Xiaoqing Xu +5
In recent years, multimodal large models have continued to improve on general benchmarks. However, in real-world content moderation and adversarial settings, mainstream models stil…