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SelfCompact reveals that language models can autonomously manage context decay, achieving up to 18.1 points improvement in performance while cutting token costs by 30-70%.
Document LoRA can recover up to 21 ROUGE-L points when context is scarce, redefining its role in memory architecture for question answering.
Agentic harnesses can significantly enhance LLM performance on deontic reasoning tasks, but not without introducing risks of degradation in numerical accuracy.
