🔗 Who cites «Extracting Commonsense Properties from Embeddings with Limited Human Guidance»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Extracting Commonsense Properties from Embeddings with Limited Human Guidance»

1. oLMpics — On what Language Model Pre-training CapturesTransactions of the Association for Computational Linguistics (TACL)Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.2019 · 440 citations
2. Do NLP Models Know Numbers? Probing Numeracy in EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Wallace, Yizhong Wang, Sujian Li, et al.2019 · 352 citations
3. Generative Data Augmentation for Commonsense ReasoningFindings of the Association for Computational LinguisticsYiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.2020 · 198 citations
4. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and ApproachesarXiv:1904.01172Shane Storks, Qiaozi Gao, Joyce Y. Chai2019 · 135 citations
5. Do Language Embeddings capture Scales?Findings of the Association for Computational LinguisticsXikun Zhang, Deepak Ramachandran, Ian Tenney, et al.2020 · 75 citations
6. How Pre-trained Word Representations Capture Commonsense Physical ComparisonsWorkshop on Commonsense Inference in Natural Language ProcessingPranav Goel, Shi Feng, Jordan Boyd-Graber2019 · 12 citations

5 more papers of our library cite it; they have no page here yet.

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