ATEST adapts LLM test-time sampling to live GPU energy
On four A100 datasets, ATEST-Online stayed inside the energy budget and tied or led accuracy as load rose.
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On four A100 datasets, ATEST-Online stayed inside the energy budget and tied or led accuracy as load rose.
Semantic Behavioral Watermarking marks LLM-agent actions so provenance survives paraphrasing and resists forged trajectories.
RegLLM measures escalation, grounding, and unsafe actions for regulated agents, but only at smoke scale.
AlignOPSD fixes decision-timestamp mismatch in on-policy distillation, beating GRPO by 5.5–8.7% on agent tasks.
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