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06/01/2023
Differentiable Tree Operations Promote Compositional Generalization
In the context of structure-to-structure transformation tasks, learning ...
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12/21/2022
Uncontrolled Lexical Exposure Leads to Overestimation of Compositional Generalization in Pretrained Models
Human linguistic capacity is often characterized by compositionality and...
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08/11/2022
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages
Machine translation has seen rapid progress with the advent of Transform...
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05/02/2022
Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systems
What explains the dramatic progress from 20th-century to 21st-century AI...
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11/18/2021
How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN
Current language models can generate high-quality text. Are they simply ...
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10/24/2021
Distributed neural encoding of binding to thematic roles
A framework and method are proposed for the study of constituent composi...
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10/24/2021
Scalable knowledge base completion with superposition memories
We present Harmonic Memory Networks (HMem), a neural architecture for kn...
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06/02/2021
Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization
Abstractive summarization, the task of generating a concise summary of i...
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05/19/2021
Compositional Processing Emerges in Neural Networks Solving Math Problems
A longstanding question in cognitive science concerns the learning mecha...
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11/18/2020
Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language
Neuro-symbolic representations have proved effective in learning structu...
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06/29/2020
Universal linguistic inductive biases via meta-learning
How do learners acquire languages from the limited data available to the...
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10/25/2019
HUBERT Untangles BERT to Improve Transfer across NLP Tasks
We introduce HUBERT which combines the structured-representational power...
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10/21/2019
Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Neural networks (NNs) are able to perform tasks that rely on composition...
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10/15/2019
Enhancing the Transformer with Explicit Relational Encoding for Math Problem Solving
We incorporate Tensor-Product Representations within the Transformer in ...
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10/05/2019
Natural- to formal-language generation using Tensor Product Representations
Generating formal-language represented by relational tuples, such as Lis...
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12/20/2018
RNNs Implicitly Implement Tensor Product Representations
Recurrent neural networks (RNNs) can learn continuous vector representat...
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11/02/2018
Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations
Neural models of Knowledge Base data have typically employed composition...
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10/29/2018
A Simple Recurrent Unit with Reduced Tensor Product Representations
idely used recurrent units, including Long-short Term Memory (LSTM) and ...
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10/29/2018
Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations
Widely used recurrent units, including Long-short Term Memory (LSTM) and...
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09/20/2018
Predicting Argumenthood of English Preposition Phrases
Distinguishing between core and non-core dependents (i.e., arguments and...
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03/10/2018
Learning and analyzing vector encoding of symbolic representations
We present a formal language with expressions denoting general symbol st...
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01/04/2018
Discrete symbolic optimization and Boltzmann sampling by continuous neural dynamics: Gradient Symbolic Computation
Gradient Symbolic Computation is proposed as a means of solving discrete...
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10/29/2017
A Neural-Symbolic Approach to Natural Language Tasks
Deep learning (DL) has in recent years been widely used in natural langu...
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09/26/2017
Tensor Product Generation Networks for Deep NLP Modeling
We present a new approach to the design of deep networks for natural lan...
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09/26/2017
Tensor Product Generation Networks
We present a new tensor product generation network (TPGN) that generates...
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05/23/2017
Question-Answering with Grammatically-Interpretable Representations
We introduce an architecture, the Tensor Product Recurrent Network (TPRN...
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01/12/2016
Basic Reasoning with Tensor Product Representations
In this paper we present the initial development of a general theory for...
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11/19/2015