mlsanityData to 14 Oct 2026

Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention

arXiv 1605.09090 ↗First posted 30 May 2016cs.CLcited by 23

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Abstract (arXiv)

In this paper, we proposed a sentence encoding-based model for recognizing text entailment. In our approach, the encoding of sentence is a two-stage process. Firstly, average pooling was used over word-level bidirectional LSTM (biLSTM) to generate a first-stage sentence representation. Secondly, attention mechanism was employed to replace average pooling on the same sentence for better representations. Instead of using target sentence to attend words in source sentence, we utilized the sentence's first-stage representation to attend words appeared in itself, which is called "Inner-Attention" in our paper . Experiments conducted on Stanford Natural Language Inference (SNLI) Corpus has proved the effectiveness of "Inner-Attention" mechanism. With less number of parameters, our model outperformed the existing best sentence encoding-based approach by a large margin.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 May 2016.

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Citing papers per year: 2021: 9; 2022: 5; 2023: 3; 2024: 3; 2025: 3.

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  1. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 51
  2. 2021Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Taskscited by 32
  3. 2023Pushing the Limits of ChatGPT on NLP Taskscited by 27
  4. 2021Lifelong Learning of Hate Speech Classification on Social Mediacited by 14
  5. 2022Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 13
  6. 2021Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extractioncited by 11
  7. 2024Comateformer: Combined Attention Transformer for Semantic Sentence Matchingcited by 9
  8. 2022AlignVE: Visual Entailment Recognition Based on Alignment Relationscited by 5
  9. 2021MIPO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learningcited by 4
  10. 2022Machine Learning in Access Control: A Taxonomy and Surveycited by 3
  11. 2021LadRa-Net: Locally-Aware Dynamic Re-read Attention Net for Sentence Semantic Matchingcited by 2
  12. 2024Review of deep learning models for crypto price prediction: implementation and evaluationcited by 2
11 more
  1. 2024Hyperbolic sentence representations for solving Textual Entailmentcited by 2
  2. 2021Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimationcited by 1
  3. 2022Compliance Checking with NLI: Privacy Policies vs. Regulationscited by 1
  4. 2023Bitformer: An efficient Transformer with bitwise operation-based attention for Big Data Analytics at low-cost low-precision devicescited by 1
  5. 2025Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generationcited by 1
  6. 2021DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matchingcited by 0
  7. 2021Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervisioncited by 0
  8. 2022Integrating Dependency Tree Into Self-attention for Sentence Representationcited by 0
  9. 2023CRL+: A Novel Semi-Supervised Deep Active Contrastive Representation Learning-Based Text Classification Model for Insurance Datacited by 0
  10. 2025Using External knowledge to Enhanced PLM for Semantic Matchingcited by 0
  11. 2025Boosting Neural Language Inference via Cascaded Interactive Reasoningcited by 0