Character distribution patterns differ between humans and AI in domain-specific ways, enabling improved AI text detection via the new LD-Score when combined with existing tools on the MDTA benchmark.
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WISP suppresses wasted drafting time and verification interference in edge-cloud speculative LLM serving through dynamic drafting and SLO-aware batching, delivering up to 2.1x capacity and 1.94x goodput gains over centralized and prior baselines.
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Beyond Perplexity: Character Distribution Signatures and the MDTA Benchmark for AI Text Detection
Character distribution patterns differ between humans and AI in domain-specific ways, enabling improved AI text detection via the new LD-Score when combined with existing tools on the MDTA benchmark.
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WISP: Waste- and Interference-Suppressed Distributed Speculative LLM Serving at the Edge via Dynamic Drafting and SLO-Aware Batching
WISP suppresses wasted drafting time and verification interference in edge-cloud speculative LLM serving through dynamic drafting and SLO-aware batching, delivering up to 2.1x capacity and 1.94x goodput gains over centralized and prior baselines.