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Yuang Qi

4 accepted papers

2026

SWIFT: Sliding Window Reconstruction for Few-Shot Training-Free Generated Video Attribution

CVPR 2026

Recent advancements in video generation technologies have been significant, resulting in their widespread application across multiple domains. However, concerns have been mounting over the potential misuse of generated content. Tracing the origin of generated videos has become crucial to mitigate po

Cited by 0SourcecodeScholar
2025

Provably Secure Image Robust Steganography via Cross-modal Error Correction

AAAI 2025technical

The rapid development of image generation models has facilitated the widespread dissemination of generated images on social networks, creating favorable conditions for provably secure image steganography. However, existing methods face issues such as low quality of generated images and lack of sema…

Cited by 0SourcePDFScholar
2025

STEAD: Robust Provably Secure Linguistic Steganography with Diffusion Language Model

NeurIPS 2025poster

Recent provably secure linguistic steganography (PSLS) methods rely on mainstream autoregressive language models (ARMs) to address historically challenging tasks, that is, to disguise covert communication as ``innocuous'' natural language communication. However, due to the characteristic of sequen…

Cited by 0SourceScholar
2024

DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection

NeurIPS 2024poster

Large language models (LLMs) have the potential to generate texts that pose risks of misuse, such as plagiarism, planting fake reviews on e-commerce platforms, or creating inflammatory false tweets. Consequently, detecting whether a text is generated by LLMs has become increasingly important. Existi…

Cited by 3SourcePDFScholar