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Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...
Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been ...
Background: Dysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely c ...
Fuzzers aware of the input grammar can explore deeper program states using grammar-aware mutations. Existing grammar-aware fuzzers are ineffective at synthesizing complex bug triggers due to: (i) grammars introducing a sampling bias during input generation ...
Procedural shape grammars are powerful tools for the automatic generation of highly detailed 3D content from a set of descriptive rules. It is easy to encode variations in stochastic and parametric grammars, and an uncountable number of models can be gener ...
We propose the Recursive Non-autoregressive Graph-to-graph Transformer architecture (RNG-Tr) for the iterative refinement of arbitrary graphs through the recursive application of a non-autoregressive Graph-to-Graph Transformer and apply it to syntactic dep ...
The newly emerged and quickly growing science of nanotechnology has been recognized as one of ``the twenty-first century's great leaps forward in scientific knowledge''. Self-assembly provides a powerful enabling technique for nanotechnology by providing a ...
Automatically identifying implicit discourse relations requires an in-depth semantic understanding of the text fragments involved in such relations. While early work investigated the usefulness of different classes of input features, current state-of-the-a ...
Programmable stochastic self-assembly of modular robots provides promising means to formation of structures at different scales. One way to address the design of dedicated control rulesets for self-assembling robotic modules is to leverage formalisms based ...
For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...