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ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language [article]

Oyvind Tafjord, Bhavana Dalvi Mishra, Peter Clark
2021 arXiv   pre-print
In this work we show that a generative model, called ProofWriter, can reliably generate both implications of a theory and the natural language proof(s) that support them.  ...  Transformers have been shown to emulate logical deduction over natural language theories (logical rules expressed in natural language), reliably assigning true/false labels to candidate implications.  ...  The ProofWriter datasets are available at https://allenai.org/data/proofwriter Appendix: ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language A Datasets: Additional  ... 
arXiv:2012.13048v2 fatcat:gidtqqoeuvahdclhxipq6vhwsq

Towards General Natural Language Understanding with Probabilistic Worldbuilding [article]

Abulhair Saparov, Tom M. Mitchell
2021 arXiv   pre-print
question-answering datasets: (1) ProofWriter and (2) a new dataset we call FictionalGeoQA, designed to be more representative of real language but still simple enough to focus on evaluating reasoning  ...  PWM is Bayesian, designed specifically to be able to generalize to new domains and new tasks.  ...  to capture the meaning of declarative and interrogative sentences in natural language.  ... 
arXiv:2105.02486v2 fatcat:wmr6wtyrxvcijg2us5it5mmafq

DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models [article]

Gregor Betz, Kyle Richardson
2021 arXiv   pre-print
In this paper, we present and implement a multi-dimensional, modular framework for performing deep argument analysis (DeepA2) using current pre-trained language models (PTLMs).  ...  premises and conclusions, formalizes inferences, and coherently links the logical reconstruction to the source text.  ...  Generating implications, proofs, and abductive statements Miller, T. 2019.  ... 
arXiv:2110.01509v2 fatcat:dvqi6kw2yzhflojy2lusxoy674