Natural language reasoning, a survey
This survey paper proposes a clearer view of natural language reasoning in the field of
Natural Language Processing (NLP), both conceptually and practically. Conceptually, we …
Natural Language Processing (NLP), both conceptually and practically. Conceptually, we …
State-of-the-art generalisation research in NLP: a taxonomy and review
The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …
Proofver: Natural logic theorem proving for fact verification
Fact verification systems typically rely on neural network classifiers for veracity prediction,
which lack explainability. This paper proposes ProoFVer, which uses a seq2seq model to …
which lack explainability. This paper proposes ProoFVer, which uses a seq2seq model to …
Natural language deduction through search over statement compositions
In settings from fact-checking to question answering, we frequently want to know whether a
collection of evidence (premises) entails a hypothesis. Existing methods primarily focus on …
collection of evidence (premises) entails a hypothesis. Existing methods primarily focus on …
Fairr: Faithful and robust deductive reasoning over natural language
Transformers have been shown to be able to perform deductive reasoning on a logical
rulebase containing rules and statements written in natural language. Recent works show …
rulebase containing rules and statements written in natural language. Recent works show …
Summarization programs: Interpretable abstractive summarization with neural modular trees
Current abstractive summarization models either suffer from a lack of clear interpretability or
provide incomplete rationales by only highlighting parts of the source document. To this end …
provide incomplete rationales by only highlighting parts of the source document. To this end …
Metgen: A module-based entailment tree generation framework for answer explanation
Knowing the reasoning chains from knowledge to the predicted answers can help construct
an explainable question answering (QA) system. Advances on QA explanation propose to …
an explainable question answering (QA) system. Advances on QA explanation propose to …
RECKONING: reasoning through dynamic knowledge encoding
Recent studies on transformer-based language models show that they can answer
questions by reasoning over knowledge provided as part of the context (ie, in-context …
questions by reasoning over knowledge provided as part of the context (ie, in-context …
Abductionrules: Training transformers to explain unexpected inputs
Transformers have recently been shown to be capable of reliably performing logical
reasoning over facts and rules expressed in natural language, but abductive reasoning …
reasoning over facts and rules expressed in natural language, but abductive reasoning …
Logical reasoning over natural language as knowledge representation: A survey
Logical reasoning is central to human cognition and intelligence. It includes deductive,
inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal …
inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal …