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nlp:entailment [2023/02/02 04:15] – [Datasets] jmflanignlp:entailment [2023/06/15 07:36] (current) – external edit 127.0.0.1
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   * [[https://arxiv.org/pdf/1704.05426.pdf|Williams et al 2017 - A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference]] MNLI dataset   * [[https://arxiv.org/pdf/1704.05426.pdf|Williams et al 2017 - A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference]] MNLI dataset
   * [[https://arxiv.org/pdf/2009.14505.pdf|Joshi et al 2020 - TaxiNLI: Taking a Ride up the NLU Hill]]   * [[https://arxiv.org/pdf/2009.14505.pdf|Joshi et al 2020 - TaxiNLI: Taking a Ride up the NLU Hill]]
-  * [[https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.251.pdf|Stacey et al 2022 - Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models]]+  * **[[https://aclanthology.org/2022.emnlp-main.251.pdf|Stacey et al 2022 - Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models]]** 
 + 
 +=== Natural Language Explanations === 
 +See also [[nlp:explainability#Natural Language Explanations]] 
 +  * [[https://arxiv.org/pdf/1812.01193.pdf|Camburu et al 2018 - e-SNLI: Natural Language Inference with Natural Language Explanations]] 
 +  * [[https://aclanthology.org/2020.acl-main.771.pdf|Kumar & Talukdar 2020 - NILE: Natural Language Inference with Faithful Natural Language Explanations]] Doesn't beat the RoBERTa baseline 
 +  * [[https://arxiv.org/pdf/2012.09157.pdf|Zhao et al 2020 - LIREx: Augmenting Language Inference with Relevant Explanation]] Improves upon NILE, beats RoBERTa baseline
  
 ==== Datasets ==== ==== Datasets ====
   * SNLI: [[https://nlp.stanford.edu/projects/snli/|Stanford Natural Language Inference (SNLI) Corpus]] paper: [[https://arxiv.org/pdf/1508.05326.pdf|Bowman 2015]]   * SNLI: [[https://nlp.stanford.edu/projects/snli/|Stanford Natural Language Inference (SNLI) Corpus]] paper: [[https://arxiv.org/pdf/1508.05326.pdf|Bowman 2015]]
-    * SNLI-hard (from [[https://arxiv.org/pdf/1803.02324.pdf|Gururangan et al 2018 - Annotation Artifacts in Natural Language Inference Data]])+    * SNLI-hard, hard examples from SNLI (from [[https://arxiv.org/pdf/1803.02324.pdf|Gururangan et al 2018 - Annotation Artifacts in Natural Language Inference Data]])
   * MNLI: [[https://cims.nyu.edu/~sbowman/multinli/|Multi-Genre NLI Corpus]] paper: [[https://arxiv.org/pdf/1704.05426.pdf|Williams 2017]]   * MNLI: [[https://cims.nyu.edu/~sbowman/multinli/|Multi-Genre NLI Corpus]] paper: [[https://arxiv.org/pdf/1704.05426.pdf|Williams 2017]]
 +  * e-SNLI [[https://arxiv.org/pdf/1812.01193.pdf|paper]]
   * SICK: [[https://marcobaroni.org/composes/sick.html|Sentences Involving Compositional Knowledge]] paper: [[https://aclanthology.org/L14-1314/|Marelli 2014]] Used in a lot a papers recently, see for example [[https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.251.pdf|Stacey 2022]]   * SICK: [[https://marcobaroni.org/composes/sick.html|Sentences Involving Compositional Knowledge]] paper: [[https://aclanthology.org/L14-1314/|Marelli 2014]] Used in a lot a papers recently, see for example [[https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.251.pdf|Stacey 2022]]
  
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   * In Question Answering   * In Question Answering
     * [[https://aclanthology.org/2021.findings-emnlp.324.pdf|Chen et al 2021 - Can NLI Models Verify QA Systems’ Predictions?]]     * [[https://aclanthology.org/2021.findings-emnlp.324.pdf|Chen et al 2021 - Can NLI Models Verify QA Systems’ Predictions?]]
 +
 +===== Types of Entailment =====
 +{{media:nli.png}}\\
 +Figure from [[https://arxiv.org/pdf/2109.08927.pdf|Wu 2021]] and [[https://aclanthology.org/W09-3714.pdf|MacCartney and Manning 2009]].
  
 ===== Related Pages ===== ===== Related Pages =====
 +  * [[nlp:explainability#Natural Language Explanations]]
   * [[Paraphrase]]   * [[Paraphrase]]
   * [[Semantics]]   * [[Semantics]]
  
  
nlp/entailment.1675311326.txt.gz · Last modified: 2023/06/15 07:36 (external edit)

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