Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search (2026.acl-long)
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| Challenge: | Controllable summarization is a form of outputs that tailors summaries to user-specified attributes. |
| Approach: | They propose an adaptive planning framework that reframes the task as planning the order of sequential attribute control with a customized Monte Carlo Tree Search. |
| Outcome: | The proposed framework surpasses LLM-based self-planning models and fine-tuned baselines in multi-attribute controllable summarization. |
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