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A Convolutional Neural Network Based Approach to Recognize Bangla Spoken Digits from Speech Signal ...
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Thought Flow Nets: From Single Predictions to Trains of Model Thought ...
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Comparing Approaches to Dravidian Language Identification ...
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Speaking clearly improves speech segmentation by statistical learning under optimal listening conditions
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In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 12, No 1 (2021); 14 ; 1868-6354 (2021)
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Recognizing lexical units in low-resource language contexts with supervised and unsupervised neural networks
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In: https://hal.archives-ouvertes.fr/hal-03429051 ; [Research Report] LACITO (UMR 7107). 2021 (2021)
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Translating the Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings ...
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MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System ...
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Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales ...
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Contextual Sentence Classification: Detecting Sustainability Initiatives in Company Reports ...
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Tripartitions of the first person space (Tamil speakers, Condition 1) ...
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Compositional Processing Emerges in Neural Networks Solving Math Problems ...
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Abstract:
A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations (e.g., auditory speech), and use this knowledge to guide the composition of simpler meanings into complex wholes. Recent progress in artificial neural networks has shown that when large models are trained on enough linguistic data, grammatical structure emerges in their representations. We extend this work to the domain of mathematical reasoning, where it is possible to formulate precise hypotheses about how meanings (e.g., the quantities corresponding to numerals) should be composed according to structured rules (e.g., order of operations). Our work shows that neural networks are not only able to infer something about the structured relationships implicit in their training data, but can also deploy this knowledge to guide the composition of individual meanings into composite ... : 7 pages, 2 figures, Accepted to CogSci 2021 for poster presentation ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://arxiv.org/abs/2105.08961 https://dx.doi.org/10.48550/arxiv.2105.08961
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Measuring and Improving BERT's Mathematical Abilities by Predicting the Order of Reasoning ...
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An empirical analysis of phrase-based and neural machine translation ...
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ProtAugment: Unsupervised diverse short-texts paraphrasing for intent detection meta-learning ...
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Updater-Extractor Architecture for Inductive World State Representations ...
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Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? ...
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multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning ...
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Word-level Human Interpretable Scoring Mechanism for Novel Text Detection Using Tsetlin Machines ...
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Exceeding the Limits of Visual-Linguistic Multi-Task Learning ...
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