Fetching the paper…
Reading the bibliography…
Acquiring commonsense knowledge and reasoning is an important goal in modern NLP research.
Hartigan JA, Wong MA (1979) Algorithm as 136: A k-means clustering algorithm. Journal of the Royal Statistical Society Series C (Applied Statistics) 28(1):100–108, URL http://www.jstor.org/stable/2346830
1979
Earlier work this paper cites.
Smedslund J (1982) Common sense as psychosocial reality: A reply to sjöberg. Scandinavian Journal of Psychology 23(1):79–82
1982
Earlier work this paper cites.
Ladkin PB (1986) Time representation: A taxonomy of internal relations. In: AAAI, pp 360–366
1986
Earlier work this paper cites.
Diederich J, Ruhmann I, May M (1987) Kriton: a knowledge-acquisition tool for expert systems. International Journal of Man-Machine Studies 26(1):29–40
1987
Earlier work this paper cites.
Lenat DB (1995) Cyc: A large-scale investment in knowledge infrastructure. Commun ACM 38(11):33–38, DOI 10.1145/219717.219745
1995
Earlier work this paper cites.
Miller GA (1995) Wordnet: A lexical database for english 38(11):39–41, DOI 10.1145/219717.219748
1995
Earlier work this paper cites.
Pinto J, Reiter R (1995) Reasoning about time in the situation calculus. Annals of Mathematics and Artificial Intelligence 14:251–268
1995
Earlier work this paper cites.
Jain AK, Murty MN, Flynn PJ (1999) Data clustering: A review. ACM Comput Surv 31(3):264–323, DOI 10.1145/331499.331504
1999
Earlier work this paper cites.
King GJ, Richards RR, Zuckerman JD, Blasier R, Dillman C, Friedman RJ, Gartsman GM, Iannotti JP, Murnahan JP, Mow VC, et al. (1999) A standardized method for assessment of elbow function. Journal of shoulder and elbow surgery 8(4):351–354
1999
Earlier work this paper cites.
Narayanan S (2000) Reasoning about actions in narrative understanding. Proceedings of the 16th International Joint Conference on Artificial Intelligence
2000
Earlier work this paper cites.
Hobbs JR, Gordon AS (2005) Toward a large-scale formal theory of commonsense psychology for metacognition. In: AAAI Spring Symposium: Metacognition in Computation, pp 49–54
2005
Earlier work this paper cites.
Backstrom L, Huttenlocher D, Kleinberg J, Lan X (2006) Group formation in large social networks: Membership, growth, and evolution. vol 2006, pp 44–54, DOI 10.1145/1150402.1150412
2006
Earlier work this paper cites.
Havasi C, Speer R, Alonso J (2007) Conceptnet 3: a flexible, multilingual semantic network for common sense knowledge. In: Recent advances in natural language processing, Citeseer, pp 27–29
2007
Earlier work this paper cites.
Bollacker K, Evans C, Paritosh P, Sturge T, Taylor J (2008) Freebase: a collaboratively created graph database for structuring human knowledge. In: SIGMOD Conference
2008
Earlier work this paper cites.
Van der Maaten L, Hinton G (2008) Visualizing data using t-sne. Journal of machine learning research 9(11)
2008
Earlier work this paper cites.
Tang L, Liu H (2009) Scalable learning of collective behavior based on sparse social dimensions. In: CIKM
2009
Earlier work this paper cites.
Havasi C, Speer R, Arnold K, Lieberman H, Alonso J, Moeller J (2010) Open mind common sense: Crowd-sourcing for common sense. In: Proceedings of the 2nd AAAI Conference on Collaboratively-Built Knowledge Sources and Artificial Intelligence, AAAI Press, AAAIWS’10-02, p 53
2010
Earlier work this paper cites.
Hobbs JR, Gordon AS (2010) Goals in a formal theory of commonsense psychology. In: FOIS, pp 59–72
2010
Earlier work this paper cites.
Nickel M, Tresp V, Kriegel HP (2011) A three-way model for collective learning on multi-relational data. pp 809–816
2011
Earlier work this paper cites.
Roemmele M, Bejan C, Gordon A (2011) Choice of plausible alternatives: An evaluation of commonsense causal reasoning
2011
Earlier work this paper cites.
Kidd A (2012) Knowledge acquisition for expert systems: A practical handbook. Springer Science & Business Media
2012
Earlier work this paper cites.
Bordes A, Usunier N, Garcia-Duran A, Weston J, Yakhnenko O (2013) Translating embeddings for modeling multi-relational data. In: Burges CJC, Bottou L, Welling M, Ghahramani Z, Weinberger KQ (eds) Advances in Neural Information Processing Systems 26, Curran Associates, Inc., pp 2787–2795, URL http://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf
2013
Earlier work this paper cites.
Rajagopal D, Cambria E, Olsher D, Kwok K (2013) A graph-based approach to commonsense concept extraction and semantic similarity detection. In: Proceedings of the 22nd International Conference on World Wide Web, pp 565–570
2013
Earlier work this paper cites.
Speer R, Havasi C (2013) Conceptnet 5: A large semantic network for relational knowledge. The people’s web meets NLP, theory and applications of natural language processing pp 161–176
2013
Earlier work this paper cites.
Weston J, Bordes A, Yakhnenko O, Usunier N (2013) Connecting language and knowledge bases with embedding models for relation extraction. EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
2013
Cited alongside, same era.
Angeli G, Manning C (2014) Naturalli: Natural logic inference for common sense reasoning. pp 534–545, DOI 10.3115/v1/D14-1059
2014
Cited alongside, same era.
Lehmann J, Isele R, Jakob M, Jentzsch A, Kontokostas D, Mendes P, Hellmann S, Morsey M, Van Kleef P, Auer S, Bizer C (2014) Dbpedia - a large-scale, multilingual knowledge base extracted from wikipedia. Semantic Web Journal 6, DOI 10.3233/SW-140134
2014
Cited alongside, same era.
Mueller ET (2014) Commonsense Reasoning: An Event Calculus Based Approach, 2nd edn. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA
2014
Cited alongside, same era.
Chen M, Tian Y, Chang KW, Skiena S, Zaniolo C (2018) Co-training embeddings of knowledge graphs and entity descriptions for cross-lingual entity alignment. arXiv preprint arXiv:180606478
2018
Later among the works it cites.
Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:181004805
2018
Later among the works it cites.
Kejriwal M (2019) Domain-Specific Knowledge Graph Construction. Springer
2019
Later among the works it cites.
Lerer A, Wu L, Shen J, Lacroix T, Wehrstedt L, Bose A, Peysakhovich A (2019) PyTorch-BigGraph: A Large-scale Graph Embedding System. In: Proceedings of the 2nd SysML Conference, Palo Alto, CA, USA
2019
Later among the works it cites.
Lin BY, Chen X, Chen J, Ren X (2019) Kagnet: Knowledge-aware graph networks for commonsense reasoning. arXiv preprint arXiv:190902151
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Perozzi B, Al-Rfou R, Skiena S (2014) Deepwalk: Online learning of social representations. In: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pp 701–710
2014
Cited alongside, same era.
Rajabi E, Sanchez-Alonso S, Sicilia MA (2014) Analyzing broken links on the web of data: An experiment with dbpedia. Journal of the Association for Information Science and Technology 65(8):1721–1727
2014
Cited alongside, same era.
Wang Z, Zhang J, Feng J, Chen Z (2014) Knowledge graph embedding by translating on hyperplanes. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, AAAI Press, AAAI’14, pp 1112–1119
2014
Cited alongside, same era.
Bandyopadhyay S (2015) Unsupervised Classification. Springer Publishing Company, Incorporated
2015
Cited alongside, same era.
Davis E, Marcus G (2015) Commonsense reasoning and commonsense knowledge in artificial intelligence. Communications of the ACM 58:92–103, DOI 10.1145/2701413
2015
Cited alongside, same era.
Färber M, Ell B, Menne C, Rettinger A (2015) A comparative survey of dbpedia, freebase, opencyc, wikidata, and yago. Semantic Web Journal 1(1):1–5
2015
Cited alongside, same era.
He S, Liu K, Ji G, Zhao J (2015) Learning to represent knowledge graphs with gaussian embedding. pp 623–632, DOI 10.1145/2806416.2806502
2015
Cited alongside, same era.
Hirschberg J, Manning CD (2015) Advances in natural language processing. Science 349(6245):261–266, DOI 10.1126/science.aaa8685
2015
Cited alongside, same era.
2019
Later among the works it cites.
Sap M, Rashkin H, Chen D, Bras R, Yejin C (2019) Social iqa: Commonsense reasoning about social interactions. pp 4453–4463, DOI 10.18653/v1/D19-1454
2019
Later among the works it cites.
Storks S, Gao Q, Chai JY (2019) Commonsense reasoning for natural language understanding: A survey of benchmarks, resources, and approaches. arXiv preprint arXiv:190401172 pp 1–60
2019
Later among the works it cites.
Sun Z, Deng ZH, Nie JY, Tang J (2019) Rotate: Knowledge graph embedding by relational rotation in complex space. In: International Conference on Learning Representations, URL https://openreview.net/forum?id=HkgEQnRqYQ
2019
Later among the works it cites.
Wen Zhang LWJCHZWZAB Bibek Paudel, Chen H (2019) Iteratively learning embeddings and rules for knowledge graph reasoning. In: 2019 World Wide Web Conference (WWW’19)
2019
Later among the works it cites.
Yuan C, Yang H (2019) Research on k-value selection method of k-means clustering algorithm. J 2:226–235, DOI 10.3390/j2020016
2019
Later among the works it cites.
Zellers R, Holtzman A, Bisk Y, Farhadi A, Yejin C (2019) Hellaswag: Can a machine really finish your sentence? pp 4791–4800, DOI 10.18653/v1/P19-1472
2019
Later among the works it cites.
Bisk Y, Zellers R, bras R, Gao J, Yejin C (2020) Piqa: Reasoning about physical commonsense in natural language. Proceedings of the AAAI Conference on Artificial Intelligence 34:7432–7439, DOI 10.1609/aaai.v34i05.6239
2020
Later among the works it cites.
Floridi L, Chiriatti M (2020) Gpt-3: Its nature, scope, limits, and consequences. Minds and Machines 30(4):681–694
2020
Later among the works it cites.
Khashabi D, Khot T, Sabharwal A, Tafjord O, Clark P, Hajishirzi H (2020) Unifiedqa: Crossing format boundaries with a single qa system. arXiv preprint arXiv:200500700
2020
Later among the works it cites.
Kumar Y, Goel N (2020) Ai-based learning techniques for sarcasm detection of social media tweets: State-of-the-art survey. SN Computer Science 1(6):1–14
2020
Later among the works it cites.
McDermott J (2020) When and why metaheuristics researchers can ignore ?no free lunch? theorems. SN Computer Science 1(1):1–18
2020
Later among the works it cites.
Nayak NV, Bach SH (2020) Zero-shot learning with common sense knowledge graphs. arXiv preprint arXiv:200610713
2020
Later among the works it cites.
Nie Y, Williams A, Dinan E, Bansal M, Weston J, Kiela D (2020) Adversarial NLI: A new benchmark for natural language understanding. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics
2020
Later among the works it cites.
Sap M, Shwartz V, Bosselut A, Choi Y, Roth D (2020) Commonsense reasoning for natural language processing. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, Association for Computational Linguistics, Online, pp 27–33, DOI 10.18653/v1/2020.acl-tutorials.7
2020
Later among the works it cites.
Song HJ, Kim AY, Park SB (2020) Learning translation-based knowledge graph embeddings by n-pair translation loss. Applied Sciences 10:3964, DOI 10.3390/app10113964
2020
Later among the works it cites.
Xu Y, Zhu C, Xu R, Liu Y, Zeng M, Huang X (2020) Fusing context into knowledge graph for commonsense reasoning. arXiv preprint arXiv:201204808
2020
Later among the works it cites.
Zhao F, Sun H, Jin L, Jin H (2020) Structure-augmented knowledge graph embedding for sparse data with rule learning. Computer Communications 159, DOI 10.1016/j.comcom.2020.05.017
2020
Later among the works it cites.
Devezas J, Nunes S (2021) A review of graph-based models for entity-oriented search
2021
Later among the works it cites.
Ye Q, Ren X (2021) Zero-shot learning by generating task-specific adapters. arXiv preprint arXiv:210100420
2021
Later among the works it cites.