Diffusion Language Models for Perplexity-Aware Black-Box Attacks
arXiv:2610.31558v1 Announce Type: cross Abstract: \emph{Continuous-space} attacks find prompts that trigger malicious behaviors, such as overthinking, in black-box LLMs by sampling or optimizing over a low-dimensional Gaussian latent space and decoding it to text through a \emph{random mapping} and…
Read the full story at arXiv stat.ML ↗
Timeline · 1 report
- 2026-10-23 04:00 · arXiv stat.ML
Diffusion Language Models for Perplexity-Aware Black-Box Attacks
More stories
- Perplexity and NVIDIA Researchers Introduce JOLT: a Joint Teacher-Student Reinforcement Learning Method — MarkTechPost
- Let's compare our paid AI subscriptions — r/ChatGPT
- Mica v0.5: The smartest 4B decision model is also the fastest one. 20 ms per answer, 25x faster than Jev — r/LocalLLM
- ASKING FOR HELP/BEGINNER NOOB to A.I. and ML (ChatGPT, Gemini, Claude, Perplexity) I know what A.I can and is used for, but I don’t have a strong understanding of the benefits it can provide — r/artificial
- Perplexity Computer now runs fully locally on Mac — TestingCatalog AI News
- How to Evaluate AI: Benchmarks, Perplexity, and BLEU Scores Explained — r/learnmachinelearning
- Decision models take off & Anthropic bans cruelty to Claude — Mixture of Experts (IBM)
- DeepSeek, MiniMax Win Approval for Global Use, State Media Says — Bloomberg AI
Get the daily brief of stories like this at 6:30 every morning →