activity
20242026
most citedAICrypto: Evaluating Cryptography Capabilities of Large Language Models

1 citations · 1 across the 3 of their papers we have counts for

collaborators

16 papers

cs.CR20261 cited

AICrypto: Evaluating Cryptography Capabilities of Large Language Models

Yu Wang, Yijian Liu, Liheng Ji +11

We build \textbf{AICrypto}, a comprehensive benchmark designed to evaluate the cryptography capabilities of large language models (LLMs). The benchmark comprises 135 multiple-choic…

cs.CL2026

Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap

Xuan Qi, Rongwu Xu, Zhijing Jin

Aligning large language models (LLMs) with human preferences is a critical challenge in AI research. While methods like Reinforcement Learning from Human Feedback (RLHF) and Direct…

cs.CL2026

Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network

Xin Liu, Rongwu Xu, Xinyi Jia +4

The rise of large language models (LLMs) has enabled the generation of highly persuasive spam reviews that closely mimic human writing. These reviews pose significant challenges fo…

cs.AI2025

The Singapore Consensus on Global AI Safety Research Priorities

Yoshua Bengio, Tegan Maharaj, Luke Ong +84

Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…

cs.AI2025

AI Awareness

Xiaojian Li, Haoyuan Shi, Rongwu Xu +1

Recent breakthroughs in artificial intelligence (AI) have brought about increasingly capable systems that demonstrate remarkable abilities in reasoning, language understanding, and…

cs.AI2025

Does Chain-of-Thought Reasoning Really Reduce Harmfulness from Jailbreaking?

Chengda Lu, Xiaoyu Fan, Yu Huang +3

Jailbreak attacks have been observed to largely fail against recent reasoning models enhanced by Chain-of-Thought (CoT) reasoning. However, the underlying mechanism remains underex…