AutoBool: Reinforcement-Learned LLM for Effective Automatic Systematic Reviews Boolean Query Generation (2026.eacl-long)
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| Challenge: | Existing approaches to generate Boolean queries for systematic reviews are limited by the lack of ground-truth best Boolesan queries. |
| Approach: | They propose a reinforcement learning framework that trains large language models to generate effective Boolean queries for medical systematic reviews. |
| Outcome: | The proposed framework outperforms zero-shot/few-shot prompting on 65 588 topics . it also matches or exceeds the effectiveness of larger GPT-based models using smaller backbones . |
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