Papers with parameter fusion framework

1 papers
Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning (2026.findings-acl)

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Challenge: Large Language Model (LLM)-based agents extend the utility of LLMs by interacting with dynamic environments.
Approach: They propose a parameter fusion framework based on directional consensus evaluation that disentangles knowledge updates through a two-stage process.
Outcome: The proposed framework disentangles knowledge updates through a two-stage process with minimal computational overhead and parameter updates.

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