{"slug": "logic-and-the-2-simplicial-transformer-2019", "title": "Logic and the 2-Simplicial Transformer (2019)", "summary": "Researchers introduced the 2-simplicial Transformer, an extension of the Transformer architecture that incorporates higher-dimensional attention generalizing dot-product attention and updates entity representations with tensor products of value vectors. The paper, submitted to arXiv on September 2, 2019, demonstrates that this architecture serves as a useful inductive bias for logical reasoning in deep reinforcement learning.", "body_md": "# Computer Science > Machine Learning\n\n[Submitted on 2 Sep 2019]\n\n# Title:Logic and the $2$-Simplicial Transformer\n\n[View PDF](/pdf/1909.00668)\n\n[HTML (experimental)](https://arxiv.org/html/1909.00668v1)\n\nAbstract:We introduce the $2$-simplicial Transformer, an extension of the Transformer which includes a form of higher-dimensional attention generalising the dot-product attention, and uses this attention to update entity representations with tensor products of value vectors. We show that this architecture is a useful inductive bias for logical reasoning in the context of deep reinforcement learning.\n\n### Current browse context:\n\ncs.LG\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\nIArxiv Recommender\n\n*(*[What is IArxiv?](https://iarxiv.org/about))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/logic-and-the-2-simplicial-transformer-2019", "canonical_source": "https://arxiv.org/abs/1909.00668", "published_at": "2026-09-01 02:29:40+00:00", "updated_at": "2026-09-01 02:52:12.422873+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-research"], "entities": ["arXiv"], "alternates": {"html": "https://wpnews.pro/news/logic-and-the-2-simplicial-transformer-2019", "markdown": "https://wpnews.pro/news/logic-and-the-2-simplicial-transformer-2019.md", "text": "https://wpnews.pro/news/logic-and-the-2-simplicial-transformer-2019.txt", "jsonld": "https://wpnews.pro/news/logic-and-the-2-simplicial-transformer-2019.jsonld"}}