| Year |
Citation |
Score |
| 2022 |
Brehm L, Cho PW, Smolensky P, Goldrick MA. PIPS: A Parallel Planning Model of Sentence Production. Cognitive Science. 46: e13079. PMID 35122314 DOI: 10.1111/cogs.13079 |
0.598 |
|
| 2021 |
Russin J, Fernandez R, Palangi H, Rosen E, Jojic N, Smolensky P, Gao J. Compositional Processing Emerges in Neural Networks Solving Math Problems. Cogsci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference. 2021: 1767-1773. PMID 34617074 |
0.672 |
|
| 2017 |
Legendre G, Smolensky P. A competition-based analysis of French anticausatives Lingvisticæ Investigationes. International Journal of Linguistics and Language Resources. 40: 25-42. DOI: 10.1075/Li.40.1.02Leg |
0.321 |
|
| 2016 |
Putnam MT, Legendre G, Smolensky P. How constrained is language mixing in bi- and uni-modal production? Epistemological Issue With Keynote Article “the Development of Bimodal Bilingualism: Implications For Linguistic Theory” by Diane Lillo-Martin, Ronice MüLler De Quadros and Deborah Chen Pichler. 6: 812-816. DOI: 10.1075/Lab.6.6.13Put |
0.307 |
|
| 2014 |
Smolensky P, Goldrick M, Mathis D. Optimization and quantization in gradient symbol systems: a framework for integrating the continuous and the discrete in cognition. Cognitive Science. 38: 1102-38. PMID 23802807 DOI: 10.1111/Cogs.12047 |
0.642 |
|
| 2013 |
Culbertson J, Smolensky P, Wilson C. Cognitive biases, linguistic universals, and constraint-based grammar learning. Topics in Cognitive Science. 5: 392-424. PMID 23703887 DOI: 10.1111/Tops.12027 |
0.403 |
|
| 2012 |
Culbertson J, Smolensky P. A Bayesian model of biases in artificial language learning: the case of a word-order universal. Cognitive Science. 36: 1468-98. PMID 22962854 DOI: 10.1111/J.1551-6709.2012.01264.X |
0.364 |
|
| 2012 |
Smolensky P. Symbolic functions from neural computation. Philosophical Transactions. Series a, Mathematical, Physical, and Engineering Sciences. 370: 3543-69. PMID 22711873 DOI: 10.1098/Rsta.2011.0334 |
0.312 |
|
| 2012 |
Culbertson J, Smolensky P, Legendre G. Learning biases predict a word order universal. Cognition. 122: 306-29. PMID 22208785 DOI: 10.1016/J.Cognition.2011.10.017 |
0.383 |
|
| 2012 |
Legendre G, Smolensky P. On the Asymmetrical Difficulty of Acquiring Person Reference in French: Production Versus Comprehension Journal of Logic, Language and Information. 21: 7-30. DOI: 10.1007/S10849-011-9150-0 |
0.314 |
|
| 2011 |
Ramadoss D, Smolensky P. Tone perception cues: Pitch targets, trajectories, or both? The Journal of the Acoustical Society of America. 129: 2420-2420. DOI: 10.1121/1.3587901 |
0.63 |
|
| 2010 |
Smolensky P. THE CONSTITUENT STRUCTURE OF CONNECTIONIST MENTAL STATES: A REPLY TO FODOR AND PYLYSHYN The Southern Journal of Philosophy. 26: 137-161. DOI: 10.1111/J.2041-6962.1988.Tb00470.X |
0.326 |
|
| 2010 |
Hogeweg L, Legendre G, Smolensky P. Kinship terminology: Polysemy or categorization? Behavioral and Brain Sciences. 33: 386-387. DOI: 10.1017/S0140525X10002062 |
0.354 |
|
| 2009 |
Berent I, Lennertz T, Smolensky P, Vaknin V. Listeners' knowledge of phonological universals: Evidence from nasal clusters. Phonology. 26: 75-108. PMID 21874095 DOI: 10.1017/S0952675709001729 |
0.33 |
|
| 2009 |
Smolensky P, Dupoux E. Universals in cognitive theories of language Behavioral and Brain Sciences. 32: 468-469. DOI: 10.1017/S0140525X09990586 |
0.356 |
|
| 2008 |
Berent I, Lennertz T, Jun J, Moreno MA, Smolensky P. Language universals in human brains. Proceedings of the National Academy of Sciences of the United States of America. 105: 5321-5. PMID 18391198 DOI: 10.1073/Pnas.0801469105 |
0.325 |
|
| 2006 |
Smolensky P. Harmony in linguistic cognition. Cognitive Science. 30: 779-801. PMID 21702837 DOI: 10.1207/S15516709Cog0000_78 |
0.358 |
|
| 2004 |
Legendre G, Hagstrom P, Chen-Main J, Tao L, Smolensky P. Deriving output probabilities in child Mandarin from a Dual-Optimization grammar Lingua. 114: 1147-1185. DOI: 10.1016/J.Lingua.2003.07.004 |
0.359 |
|
| 2002 |
Jusczyk PW, Smolensky P, Allocco T. How English-Learning Infants Respond to Markedness and Faithfulness Constraints Language Acquisition. 10: 31-73. DOI: 10.1207/S15327817La1001_3 |
0.351 |
|
| 1999 |
Smolensky P. Grammar-based connectionist approaches to language Cognitive Science. 23: 589-613. DOI: 10.1207/S15516709Cog2304_9 |
0.37 |
|
| 1998 |
Tesar BB, Smolensky P. Learning optimality-theoretic grammars Lingua. 106: 161-196. DOI: 10.1016/S0024-3841(98)00033-3 |
0.658 |
|
| 1998 |
Tesar B, Smolensky P. Learnability in optimality theory Linguistic Inquiry. 29: 229-268. DOI: 10.1002/9780470756171.ch5 |
0.634 |
|
| 1997 |
Prince A, Smolensky P. Optimality: from neural networks to universal grammar. Science (New York, N.Y.). 275: 1604-10. PMID 9054349 DOI: 10.1126/Science.275.5306.1604 |
0.618 |
|
| 1990 |
Smolensky P. Representation in Connectionist Networks Intellectica. Revue De L'Association Pour La Recherche Cognitive. 9: 127-165. DOI: 10.3406/Intel.1990.882 |
0.347 |
|
| 1990 |
Smolensky P. Tensor product variable binding and the representation of symbolic structures in connectionist systems Artificial Intelligence. 46: 159-216. DOI: 10.1016/0004-3702(90)90007-M |
0.325 |
|
| 1988 |
Smolensky P. On the proper treatment of connectionism Behavioral and Brain Sciences. 11: 1-23. DOI: 10.1017/S0140525X00052432 |
0.326 |
|
| 1987 |
Smolensky P. Connectionist AI, symbolic AI, and the brain Artificial Intelligence Review. 1: 95-109. DOI: 10.1007/Bf00130011 |
0.328 |
|
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