8 papers
QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs
Junlin Zhu, Baizhou Huang, Xiaojun Wan
As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider-internal deployments, a key…
Enhancing LLM Watermark Resilience Against Both Scrubbing and Spoofing Attacks
Huanming Shen, Baizhou Huang, Xiaojun Wan
Watermarking is a promising defense against the misuse of large language models (LLMs), yet it remains vulnerable to scrubbing and spoofing attacks. This vulnerability stems from a…
Generative Evaluation of Complex Reasoning in Large Language Models
Haowei Lin, Xiangyu Wang, Ruilin Yan +7
With powerful large language models (LLMs) demonstrating superhuman reasoning capabilities, a critical question arises: Do LLMs genuinely reason, or do they merely recall answers f…
: A Black-Box Scrubbing Attack on LLM Watermarks
Baizhou Huang, Xiao Pu, Xiaojun Wan
Watermarking has emerged as a prominent technique for LLM-generated content detection by embedding imperceptible patterns. Despite supreme performance, its robustness against adver…
MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency
Junzhe Zhang, Huixuan Zhang, Xunjian Yin +4
Multimodal large language models (MLLMs) are prone to non-factual or outdated knowledge issues, which can manifest as misreading and misrecognition errors due to the complexity of…
Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistency
Baizhou Huang, Shuai Lu, Weizhu Chen +2
Large language models (LLMs) have exhibited remarkable ability in code generation. However, generating the correct solution in a single attempt still remains a challenge. Prior wor…