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cs.LG2026
Weak Ties, Strong Signals: Efficient Training Data Detection in Diffusion LLMs via Independent Token Sampling
Hongyao Yu, Tianqu Zhuang, Ziyuan Xu +4
Diffusion large language models (dLLMs) offer a compelling alternative to autoregressive models, yet they may expose sensitive training data during denoising. Detecting such usage…
cs.LG2025
LFM4Ads: Large Foundation Model for Ads Recommendation
Shangyu Zhang, Shijie Quan, Zhongren Wang +32
Recent work leverages large-scale pretrained foundation models (FMs) to transfer generalizable representations to downstream advertising tasks. Most existing approaches transfer us…