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nlp:commonsense_reasoning

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nlp:commonsense_reasoning [2022/10/12 00:58] – [General Papers] jmflanignlp:commonsense_reasoning [2023/07/25 01:07] (current) – [Datasets] jmflanig
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     * [[https://arxiv.org/pdf/1905.07830.pdf|Zellers et al 2019 - HellaSwag: Can a Machine Really Finish Your Sentence?]]     * [[https://arxiv.org/pdf/1905.07830.pdf|Zellers et al 2019 - HellaSwag: Can a Machine Really Finish Your Sentence?]]
   * [[https://arxiv.org/pdf/1811.00146.pdf|Sag et al 2018 - ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning]]   * [[https://arxiv.org/pdf/1811.00146.pdf|Sag et al 2018 - ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning]]
-  * [[https://arxiv.org/pdf/1906.05317.pdf|Bosselut et al COMET: Commonsense Transformers for Automatic Knowledge Graph Construction]] Can be used as a language model-like interface to knowledge contained in ATOMIC or ConceptNet. The “mask” tokens are padding for batch training, see [[https://github.com/atcbosselut/comet-commonsense/issues/31|here]]. [[https://mosaickg.apps.allenai.org/model_comet2020_people_events|Demo]]+  * [[https://arxiv.org/pdf/1909.00505.pdf|Feldman et al 2019 - Commonsense Knowledge Mining from Pretrained Models]] 
 +  * [[https://arxiv.org/pdf/1906.05317.pdf|Bosselut et al 2019 - COMET: Commonsense Transformers for Automatic Knowledge Graph Construction]] Can be used as a language model-like interface to knowledge contained in ATOMIC or ConceptNet. The “mask” tokens are padding for batch training, see [[https://github.com/atcbosselut/comet-commonsense/issues/31|here]]. **[[https://mosaickg.apps.allenai.org/model_comet2020_people_events|Demo]]**
   * [[https://aclanthology.org/2022.acl-long.225.pdf|Liu et al 2022 - Generated Knowledge Prompting for Commonsense Reasoning]]   * [[https://aclanthology.org/2022.acl-long.225.pdf|Liu et al 2022 - Generated Knowledge Prompting for Commonsense Reasoning]]
  
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   * [[https://arxiv.org/pdf/1811.00937.pdf|Talmor et al 2018 - CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge]]   * [[https://arxiv.org/pdf/1811.00937.pdf|Talmor et al 2018 - CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge]]
   * [[https://arxiv.org/pdf/2004.05483.pdf|Shwartz et al 2020 - Unsupervised Commonsense Question Answering with Self-Talk]]   * [[https://arxiv.org/pdf/2004.05483.pdf|Shwartz et al 2020 - Unsupervised Commonsense Question Answering with Self-Talk]]
 +
 +==== Abductive Reasoning ====
 +  * Papers
 +    * [[https://arxiv.org/pdf/1908.05739.pdf|Bhagavatula et al 2019 - Abductive Commonsense Reasoning]]
 +
  
  
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 ===== Datasets ===== ===== Datasets =====
 +A very helpful list of resources is here: [[https://cs.nyu.edu/~davise/Benchmarks/Text.html]]
 +
   * [[https://rowanzellers.com/swag/|SWAG]]    * [[https://rowanzellers.com/swag/|SWAG]] 
   * [[https://rowanzellers.com/hellaswag/|HellaSWAG]]   * [[https://rowanzellers.com/hellaswag/|HellaSWAG]]
   * Winograd Schema Challenge ([[https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html|original dataset]])   * Winograd Schema Challenge ([[https://cs.nyu.edu/~davise/papers/WinogradSchemas/WS.html|original dataset]])
   * [[https://www.tau-nlp.sites.tau.ac.il/commonsenseqa|CommonsenseQA]] [[https://arxiv.org/pdf/1811.00937.pdf|paper]]   * [[https://www.tau-nlp.sites.tau.ac.il/commonsenseqa|CommonsenseQA]] [[https://arxiv.org/pdf/1811.00937.pdf|paper]]
 +  * Abductive Reasoning Datasets
 +    * ART, $\alpha$NLI and $\alpha$NLG: 20k commonsense narrative contexts and 200k explanations (from ROCStories dataset) [[https://arxiv.org/pdf/1908.05739.pdf|paper]]
 +
 +===== Demos =====
 +  * COMET [[https://mosaickg.apps.allenai.org/model_comet2020_people_events|Demo]]
  
 ===== Tutorials ===== ===== Tutorials =====
nlp/commonsense_reasoning.1665536281.txt.gz · Last modified: 2023/06/15 07:36 (external edit)
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