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Found 6 papers, 3 papers with code
Braid: Weaving Symbolic and Neural Knowledge into Coherent Logical Explanations
Traditional symbolic reasoning engines, while attractive for their precision and explicability, have a few major drawbacks: the use of brittle inference procedures that rely on exact matching (unification) of logical terms, an inability to deal with uncertainty, and the need for a precompiled rule-base of knowledge (the "knowledge acquisition" problem).
Open-Domain Frame Semantic Parsing Using Transformers
Frame semantic parsing is a complex problem which includes multiple underlying subtasks.
SKATE: A Natural Language Interface for Encoding Structured Knowledge
In Natural Language (NL) applications, there is often a mismatch between what the NL interface is capable of interpreting and what a lay user knows how to express.
GLUCOSE: GeneraLized and COntextualized Story Explanations
As a step toward AI systems that can build similar mental models, we introduce GLUCOSE, a large-scale dataset of implicit commonsense causal knowledge, encoded as causal mini-theories about the world, each grounded in a narrative context.
