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Few-shot learning can dramatically enhance attack forensics, with DUPIN achieving superior detection accuracy using minimal labeled data.
RATrain achieves a remarkable 1.35x end-to-end speedup for LLM training on bandwidth-limited supercomputers, challenging the notion that high-bandwidth environments are necessary for efficiency.
LLM inference on supercomputers doesn't have to be a bottleneck: THInfer achieves up to 84% higher throughput than A800 GPUs by co-designing hardware-aware kernels and a communication-optimized pipeline.
LLMs still can't reliably reverse engineer stripped binaries, and REBench offers a standardized, fair-by-construction benchmark to finally measure progress.
