Differentiable Representations For Multihop Inference Rules.

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Differentiable Representations For Multihop Inference Rules - arXiv

May 24, 2019 · Abstract:We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB).

[PDF] Differentiable Representations For Multihop Inference Rules

www.semanticscholar.org › paper › Diffe...

A new operation is introduced which can be used to compositionally construct second-order multi-hop templates in a neural model, and a number of alternative ...

[1905.10417] Differentiable Representations For Multihop Inference ...

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Abstract. We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB).

Differentiable Representations For Multihop Inference Rules

www.researchgate.net › ... › Inference

We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB).

[PDF] Differentiable Convex Optimization for Explainable Multi-hop Inference

aclanthology.org › 2022.tacl-1.64....

Abstract. This paper presents Diff-Explainer, the first hybrid framework for explainable multi-hop inference that integrates explicit constraints.

Differentiable Convex Optimization for Explainable Multi-hop Inference ...

direct.mit.edu › tacl › doi › tacl_a_00508

Sep 19, 2022 · This paper presents Diff-Explainer, the first hybrid framework for explainable multi-hop inference that integrates explicit constraints with neural ...

Matthew Siegler | Papers With Code

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We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB). Paper

William W. Cohen's Papers: Inductive Logic Programming

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William W. Cohen, Haitian Sun, Alex Hofer, Matthew Siegler (2019): Differentiable Representations For Multihop Inference Rules in arxiv. Earlier version of ICLR ...

William W. Cohen | Papers With Code

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We propose a theoretical framework for formulating language model decoder algorithms with dynamic programming and information theory.

William W. Cohen's Papers: Deep Learning

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... Differentiable Representations For Multihop Inference Rules in arxiv. Earlier version of ICLR paper on NQL. William W. Cohen, Matthew Siegler, Alex Hofer ...

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