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Found 3 papers, 1 papers with code
VinVL+L: Enriching Visual Representation with Location Context in VQA
In this paper, we describe a novel method - VinVL+L - that enriches the visual representations (i. e. object tags and region features) of the State-of-the-Art Vision and Language (VL) method - VinVL - with Location information.
Ranked #10 on
Visual Question Answering (VQA)
on GQA Test2019
Semantic Parsing of Mathematics by Context-based Learning from Aligned Corpora and Theorem Proving
We study methods for automated parsing of informal mathematical expressions into formal ones, a main prerequisite for deep computer understanding of informal mathematical texts.
Machine Learner for Automated Reasoning 0.4 and 0.5
Machine Learner for Automated Reasoning (MaLARea) is a learning and reasoning system for proving in large formal libraries where thousands of theorems are available when attacking a new conjecture, and a large number of related problems and proofs can be used to learn specific theorem-proving knowledge.
