Papers with dual-path design

2 papers
HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents (2026.acl-long)

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Challenge: Existing memory systems represent conversation history as unstructured embedding vectors, retrieving information through semantic similarity.
Approach: They propose a bio-inspired memory architecture that models memory as a dynamic graph with Hebbian learning dynamics.
Outcome: The proposed architecture leverages both semantic similarity and learned associations . it can be used to build a bio-inspired memory graph with Hebbian learning dynamics .
LoRA-Guard: Parameter-Efficient Guardrail Adaptation for Content Moderation of Large Language Models (2024.emnlp-main)

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Challenge: Existing model-based guardrails have not been designed for resource-constrained computational portable devices such as mobile phones.
Approach: They propose a parameter-efficient guardrail adaptation method that relies on knowledge sharing between LLMs and guardrail models to adapt to content moderation tasks.
Outcome: The proposed method outperforms existing guardrail methods with lower parameter overhead and higher accuracy on the generative task.

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