FANDOM


(Mathematical reasoning: correct link)
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https://futurism.com/deepmind-abstract-reasoning-iq/
 
https://futurism.com/deepmind-abstract-reasoning-iq/
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== Multi-hop reasoning ==
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* HotpotQA (Yang et al. 2018)<ref>Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W. W., Salakhutdinov, R., & Manning, C. D. (2020). Hotpotqa: A dataset for diverse, explainable multi-hop question answering. ''Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018'', 2369–2380.</ref>
   
 
== Comprehension ==
 
== Comprehension ==

Latest revision as of 22:03, April 26, 2020

TODO: a survey on AI Magazine, a blogpost

https://futurism.com/deepmind-abstract-reasoning-iq/

Multi-hop reasoning Edit

  • HotpotQA (Yang et al. 2018)[1]

Comprehension Edit

Mathematical reasoning Edit

TO CATEGORIZE Edit

References Edit

  1. Yang, Z., Qi, P., Zhang, S., Bengio, Y., Cohen, W. W., Salakhutdinov, R., & Manning, C. D. (2020). Hotpotqa: A dataset for diverse, explainable multi-hop question answering. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018, 2369–2380.
  2. Frermann, L., Cohen, S. B., & Lapata, M. (2017). Whodunnit? Crime Drama as a Case for Natural Language Understanding. Retrieved from http://arxiv.org/abs/1710.11601
  3. Trischler, A., Ye, Z., Yuan, X., & Suleman, K. (2016). Natural Language Comprehension with the EpiReader. Retrieved from http://arxiv.org/abs/1606.02270
  4. Berant, J., Srikumar, V., Chen, P.-C., Linden, A. Vander, Harding, B., Huang, B., … Manning, C. D. (2014). Modeling Biological Processes for Reading Comprehension. In Empirical Methods in Natural Language Processing (EMNLP).
  5. Saxton, D., Grefenstette, E., Hill, F., & Kohli, P. (2019). Analysing mathematical reasoning abilities of neural models. ICLR 2019, 1–17. Retrieved from https://arxiv.org/pdf/1904.01557.pdf
  6. Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh. 2015.
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