Core Data of HowNet and OpenHowNet Python API
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Updated
Dec 16, 2021 - Python
Core Data of HowNet and OpenHowNet Python API
Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn
Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
Information extraction from English and German texts based on predicate logic
Semantically consistent regularizer for zero-shot learning
Modern port of Melanie Mitchell's and Douglas Hofstadter's Copycat
Universal Conceptual Cognitive Annotation (UCCA)
STREUSLE: a corpus with comprehensive lexical semantic annotation (multiword expressions, supersenses)
*SEM 2018: Learning Distributed Event Representations with a Multi-Task Approach
Abstract Meaning Representation (AMR) Hackathon
Information extraction from English and German texts based on predicate logic
Code and dataset for tracing semantic changes in Russian adjectives
[CVPR 2023] SFD2: Semantic-guided Feature Detection and Description. Embedding semantics into local features implicitly for long-term visual localization
Max-Margin Markov Graph Models for WordNet (EMNLP 2018)
[CVPR 2024] 🏡Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning
Lambda Notebook: Formal Semantics in Jupyter
Auto-CORPus pipeline developed by a University of Nottingham and Imperial College London collaboration to standardize text and table data extracted from full text publications. See Open Access publication at: https://doi.org/10.3389/fdgth.2022.788124.
A library for manipulating DMRS structures
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