{"slug": "neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent", "title": "Neural Wani: Toward Accelerating the Automated Theorem Prover wani for Dependent Type Theory", "summary": "Researchers Nanako Miyagawa, Hinari Daido, and Daisuke Bekki introduced Neural Wani, an integration of a lightweight LSTM-based neural model into the automated theorem prover wani for Dependent Type Theory, achieving a 1.41x speedup on the JSeM dataset compared to the standard non-neural baseline. The approach, presented at the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-3) in Paris, France, in July 2026, predicts applicable inference rules to guide backward proof search, with slight overhead in simpler proofs but effective acceleration in complex DTT-based proving.", "body_md": "##### Abstract\n\nThis paper proposes Neural Wani, an integration of a neural model into the automated theorem prover wani for Dependent Type Theory (DTT), aimed at accelerating proof search in natural language inference (NLI) pipelines. We implemented a lightweight LSTM-based model to predict the probability distribution of applicable inference rules and integrated it into wani’s backward inference process. Evaluation using the JSeM dataset demonstrates that Neural Wani achieves a 1.41x speedup compared to the standard non-neural baseline. Although slight overhead is observed in simpler proofs, our results indicate that neural-symbolic integration effectively guides search in complex DTT-based automated theorem proving.- Anthology ID:\n- 2026.brigap-1.2\n- Volume:\n[Proceedings of the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-3)](/volumes/2026.brigap-1/)- Month:\n- July\n- Year:\n- 2026\n- Address:\n- Paris, France\n- Editors:\n[Timothée Bernard](/people/timothee-bernard/),[Emmanuele Chersoni](/people/emmanuele-chersoni/),[Giulia Rambelli](/people/giulia-rambelli/unverified/)- Venues:\n[BriGap](/venues/brigap/)|[WS](/venues/ws/)- SIG:\n- Publisher:\n- Association for Computational Linguistics\n- Note:\n- Pages:\n- 12–21\n- Language:\n- URL:\n[https://aclanthology.org/2026.brigap-1.2/](https://aclanthology.org/2026.brigap-1.2/)- DOI:\n- Cite (ACL):\n- Nanako Miyagawa, Hinari Daido, and Daisuke Bekki. 2026.\n[Neural Wani: Toward Accelerating the Automated Theorem Prover wani for Dependent Type Theory](https://aclanthology.org/2026.brigap-1.2/). In*Proceedings of the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-3)*, pages 12–21, Paris, France. Association for Computational Linguistics. - Cite (Informal):\n[Neural Wani: Toward Accelerating the Automated Theorem Prover wani for Dependent Type Theory](https://aclanthology.org/2026.brigap-1.2/)(Miyagawa et al., BriGap 2026)- PDF:\n[https://aclanthology.org/2026.brigap-1.2.pdf](https://aclanthology.org/2026.brigap-1.2.pdf)", "url": "https://wpnews.pro/news/neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent", "canonical_source": "https://aclanthology.org/2026.brigap-1.2/", "published_at": "2026-07-31 00:00:00+00:00", "updated_at": "2026-08-04 21:51:35.474479+00:00", "lang": "en", "topics": ["machine-learning", "natural-language-processing", "artificial-intelligence"], "entities": ["Neural Wani", "wani", "JSeM", "Nanako Miyagawa", "Hinari Daido", "Daisuke Bekki", "BriGap-3"], "alternates": {"html": "https://wpnews.pro/news/neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent", "markdown": "https://wpnews.pro/news/neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent.md", "text": "https://wpnews.pro/news/neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent.txt", "jsonld": "https://wpnews.pro/news/neural-wani-toward-accelerating-the-automated-theorem-prover-wani-for-dependent.jsonld"}}