Papers with autonomous planning

2 papers
SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval (2026.findings-acl)

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Challenge: a new framework casts LLM planning as non-parametric retrieval, but high latency of inference-time search and supervised fine-tuning are limitations.
Approach: They propose a framework that casts LLM planning as non-parametric retrieval . they leverage Monte Carlo Tree Search to explore the solution space .
Outcome: Empirical results show that SGA-MCTS can match the performance of SOTA systems without task-specific fine-tuning.
Revealing the Barriers of Language Agents in Planning (2025.naacl-long)

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Challenge: Existing studies show language agents lack human-level planning abilities . limitations and mechanisms to address them remain insufficiently understood .
Approach: They apply a feature attribution study to identify key factors hindering agent planning . they identify the limited role of constraints and diminishing influence of questions .
Outcome: The proposed model achieves 15.6% on a real-world planning benchmark.

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