Introduces Parametric Memory Law as power law for LoRA memory capacity and MemFT threshold-guided optimization for better memory fidelity.
Human-inspired perspectives: A survey on ai long-term memory
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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UNVERDICTED 3representative citing papers
NEMORI is an adaptive memory distillation framework for LLM agents that transforms raw interactions into narratives and extracts insights via prediction error to decide what deserves retention.
Advocates prioritizing explicit contextual feedback in LLM-based recommender systems to improve user preference alignment and explainability.
citing papers explorer
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How LoRA Remembers? A Parametric Memory Law for LLM Finetuning
Introduces Parametric Memory Law as power law for LoRA memory capacity and MemFT threshold-guided optimization for better memory fidelity.
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What Deserves Memory: Adaptive Memory Distillation for LLM Agents
NEMORI is an adaptive memory distillation framework for LLM agents that transforms raw interactions into narratives and extracts insights via prediction error to decide what deserves retention.
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Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback
Advocates prioritizing explicit contextual feedback in LLM-based recommender systems to improve user preference alignment and explainability.