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Found 22 papers, 2 papers with code
Substructure Aware Graph Neural Networks
Despite the great achievements of Graph Neural Networks (GNNs) in graph learning, conventional GNNs struggle to break through the upper limit of the expressiveness of first-order Weisfeiler-Leman graph isomorphism test algorithm (1-WL) due to the consistency of the propagation paradigm of GNNs with the 1-WL. Based on the fact that it is easier to distinguish the original graph through subgraphs, we propose a novel framework neural network framework called Substructure Aware Graph Neural Networks (SAGNN) to address these issues.
Ranked #7 on
Graph Regression
on ZINC-500k
Query-focused Sentence Compression in Linear Time
Search applications often display shortened sentences which must contain certain query terms and must fit within the space constraints of a user interface.
Summarizing Relationships for Interactive Concept Map Browsers
We present a model which responds to such queries by returning one or more short, importance-ranked, natural language descriptions of the relationship between two requested concepts, for display in a visual interface.
DisSim: A Discourse-Aware Syntactic Text Simplification Framework for English and German
We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.
Understanding the Evolution of Circular Economy through Language Change
In this study, we propose to focus on understanding the evolution of a specific scientific concept{---}that of Circular Economy (CE){---}by analysing how the language used in academic discussions has changed semantically.
Relational Summarization for Corpus Analysis
This work introduces a new problem, relational summarization, in which the goal is to generate a natural language summary of the relationship between two lexical items in a corpus, without reference to a knowledge base.
SemEval-2017 Task 11: End-User Development using Natural Language
This task proposes a challenge to support the interaction between users and applications, micro-services and software APIs using natural language.
SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News
This paper discusses the {``}Fine-Grained Sentiment Analysis on Financial Microblogs and News{''} task as part of SemEval-2017, specifically under the {``}Detecting sentiment, humour, and truth{''} theme.
Categorization of Semantic Roles for Dictionary Definitions
Understanding the semantic relationships between terms is a fundamental task in natural language processing applications.
NNBlocks: A Deep Learning Framework for Computational Linguistics Neural Network Models
Lately, with the success of Deep Learning techniques in some computational linguistics tasks, many researchers want to explore new models for their linguistics applications.
Evaluation of Technology Term Recognition with Random Indexing
Moreover, the accomplished experiments suggest that the obtained results, to a great extent, are independent of the value of k.
