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From the 1 of 22 linked papers with an AI index.

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22 papers

cs.CR2026

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness

Jiahao Huo, Wenjie Qu, Yibo Yan +5

The paper introduces SAMark, a text watermarking method that remains detectable even after paragraph‑level paraphrasing by removing reliance on sentence order and using a hyperboli…

cs.LG2026

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks

Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1

With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…

cs.CR2026

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

Peizhi Niu, Wenjie Qu, Shangding Gu +14

Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services. They take on system-level responsibilities…

cs.CR2026

AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing

Yuexin Li, Wenjie Qu, Linyu Wu +5

Existing sentence-level watermarking methods enhance robustness to paraphrasing by anchoring watermarks in sentence semantics. However, their prefix-based designs remain vulnerable…

cs.CR2026

Echoes within the Reasoning: Stealthy and Effective Watermarking via Chain of Thought

Jiacheng Lu, Yiming Li, Tao Song +4

Large Language Models with Chain-of-Thought reasoning capabilities represent valuable intellectual property, yet existing black-box watermarking methods often trade robustness for…

cs.CR2026

GuardReasoner-Omni: A Reasoning-based Multi-modal Guardrail for Text, Image, Video, and Audio

Zhenhao Zhu, Yue Liu, Yanpei Guo +9

We present GuardReasoner-Omni, a reasoning-based guardrail model designed to moderate text, image, video, and audio data. First, we construct a comprehensive training corpus compri…