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Deobfuscation just got a whole lot easier: PUSHAN cracks virtualization-obfuscated binaries without relying on brittle trace analysis or expensive symbolic execution.
Instance-specific timestep schedules can significantly boost diffusion model performance, challenging the reliance on global discretization strategies.
Synthetic data from generative AI can mislead statistical inference if used naively, but this paper clarifies the assumptions and pitfalls to avoid, offering a roadmap for principled application.
LLMs can perfectly cluster speakers in overlapping multi-party conversations, enabling near-perfect Joint ASR-Clustering Error Rate in challenging CHiME-9 tasks.
LLMs can navigate more efficiently by retrieving relevant past trajectories and pruning irrelevant actions, even without fine-tuning.
