Sentence Pair Modeling

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (12 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
  2 Nov 2019 7 repositories listed Syntology ran 7 of 35 samples · 28 unverified
  Moreover, it is shown that reasonable performance can be obtained when ZEN is trained on a small corpus, which is important for applying pre-training techniques to scenarios with limited data.
• Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
  11 Oct 2022 1 repository listed
  Transformer-based models have achieved great success on sentence pair modeling tasks, such as answer selection and natural language inference (NLI).
• Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks
  16 Oct 2020 1 repository listed
  Bi-encoders, on the other hand, require substantial training data and fine-tuning over the target task to achieve competitive performance.
• Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding
  14 Aug 2019 1 repository listed
  In this paper, we introduce Distilled Sentence Embedding (DSE) - a model that is based on knowledge distillation from cross-attentive models, focusing on sentence-pair tasks.
• Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering
  12 Jun 2018 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  In this paper, we analyze several neural network designs (and their variations) for sentence pair modeling and compare their performance extensively across eight datasets, including paraphrase identification, semantic…
• Character-based Neural Networks for Sentence Pair Modeling
  21 May 2018 1 repository listed
  Sentence pair modeling is critical for many NLP tasks, such as paraphrase identification, semantic textual similarity, and natural language inference.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.