Neuro-Symbolic Logical Reasoning with Textual Entailment
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Demo Track. Pages 8501-8504.
https://doi.org/10.24963/ijcai.2026/989
Keywords
- AI: Natural Language Processing
- AI: Knowledge Representation and Reasoning
Abstract
Large Language Models can use logical deduction to answer natural language questions, but they remain black-boxes with potentially erroneous chains-of-thought. In this paper, we adapt VANESSA, a neuro-symbolic method for chain-of-thought verification, to reasoning-based question answering. VANESSA combines a logical reasoner with a neural textual entailment model to handle phrasing variations. Building on VANESSA, we develop a transparent, logic-based approach to answer natural language questions even with phrase variations. Our experiments across various datasets show our method is competitive with the state of the art, while also delivering proof trees for its answers. A demo interface allows users to interact with the system.
@inproceedings{ijcai2026p989,
title = {Neuro-Symbolic Logical Reasoning with Textual Entailment},
author = {Sadeddine, Zacchary and Suchanek, Fabian},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {8501--8504},
year = {2026},
month = {8},
note = {Demo Track},
doi = {10.24963/ijcai.2026/989},
url = {https://doi.org/10.24963/ijcai.2026/989},
}
TY - CPAPER TI - Neuro-Symbolic Logical Reasoning with Textual Entailment AU - Sadeddine, Zacchary AU - Suchanek, Fabian T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 8501 EP - 8504 DO - 10.24963/ijcai.2026/989 UR - https://doi.org/10.24963/ijcai.2026/989 ER -Copied
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