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Watermarking LLM-agent trajectories just got a major upgrade鈥擳RACE achieves near-perfect detection without sacrificing performance, even under aggressive adversarial conditions.
The traditional complexity of leverage-score algorithms is misleading; the real challenge lies in identification, not accuracy, allowing for a dramatic reduction in query complexity.
Despite shared legal traditions, LAUKIN reveals that drafting conventions across jurisdictions can lead to significant challenges in determining legal equivalence.
Differential privacy in language tasks is surprisingly cheap: approximate DP is free, and pure DP only reduces performance by a factor of $\min\{1,\varepsilon\}$.
Diffusion watermarks, thought to be robust, crumble under a simple stochastic resampling attack that breaks trajectory reconstruction.
