mlsanityData to 14 Oct 2026

Natural Language Inference by Tree-Based Convolution and Heuristic Matching

arXiv 1512.08422 ↗First posted 28 Dec 2015cs.CL cs.LGcited by 43

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Abstract (arXiv)

In this paper, we propose the TBCNN-pair model to recognize entailment and contradiction between two sentences. In our model, a tree-based convolutional neural network (TBCNN) captures sentence-level semantics; then heuristic matching layers like concatenation, element-wise product/difference combine the information in individual sentences. Experimental results show that our model outperforms existing sentence encoding-based approaches by a large margin.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Dec 2015.

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Citing papers per year: 2021: 19; 2022: 8; 2023: 9; 2024: 1; 2025: 1; 2026: 5.

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