Papers with planning mechanisms

2 papers
From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents (2026.findings-acl)

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Challenge: Existing plans for large language model-based agents are limited by their granularity and lack flexibility.
Approach: They propose a self-adaptive hierarchical planning mechanism that mimics human planning strategies and generates self-adapted hierarchic plans tailored to the varying difficulty levels of different tasks.
Outcome: The proposed method significantly improves task execution success rates while mitigating overthinking at the planning level, providing a flexible and efficient solution for multi-step complex decision-making tasks.
Investigating Content Planning for Navigating Trade-offs in Knowledge-Grounded Dialogue (2024.eacl-long)

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Challenge: Knowledge-grounded dialogues require a balance between being specific to what the conversation partner has said and being attributable to an underlying source document.
Approach: They propose a framework that allows to experiment with various plan variables supported by prior work . they show that metric-aware planning mechanisms are better at automatic evaluations but underperform in human judgment compared to metric agnostic mechanisms.
Outcome: The proposed framework supports metric-agnostic and metric aware content planning, but it underperforms in human judgment.

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