Neural models are by now mature technologies to be exploited for automating the argument mining tasks, despite the issue of data sparseness. This could ease much of the manual effort involved in these tasks, taking into account heterogeneous types of texts and topics. In this work, we evaluate...
In this work we investigate the possibility of actually exploiting this wealth of information. We propose and evaluate a system for automatic face annotation of image news that is fully unsupervised and does not require any prior knowledge about topic or people involved. Key feature of our ...
I found the issue in the code. When loading a merged peft model from a local path, the start and end tokens will not be appended properly (see llm2vec.py, line 138ff): def prepare_for_tokenization(self, text): if self.model.config_name_or_path == "meta-llama/Meta-Llama-3-8B-In...
High-temperature excitation can break the chemical bonds of active components such as SiO2 and Al2O3 in the recycled micropowder, and cause a part of the recycled micropowder that is not originally involved in hydration to react and generate a large amount of the network C–S–H gel. As ...
In this section, we formally define the deep representation learning problem. As Fig.2illustrates, any domain-specific MTDTL problem can be abstracted into a formal task, which is instantiated by a specific dataset with specific observations and labels. Multiple tasks and datasets are involved to ...
After trained on a large corpus from various fields, BERT has been proven very useful in fulfilling a wide range of NLP tasks [36, 37]. Some studies proposed some variants of BERT, one of which is RoBERTa [30], which uses the same network as BERT, but was trained with improved ...
NLPDE [32,33] may be converted into a set of algebraic equations using the RB equation and a traveling wave transformation. An approach for creating precise differential equation solutions is the MAEM [34]. The auxiliary equation approach has been expanded in this way. It offers a simple ...
The primary analysis involved the overall performance in classifying the swallowing and non-swallowing tasks (i.e., coarse classification). Thereupon, two fine-grained classifications (subgroup analyses) on four classes and eight classes were performed. The former involved vowel pronunciation, deep ...
The present research study aims to contribute to the literature by developing an NLP application—specifically, a TM algorithm—for the Italian natural language. This work can be an asset for grounding applications of topic modeling and can be inspiring for similar case studies in the area of ...
artificial intelligence; AI; big data; deep learning; neural networks; NLP; fuzzy logic; expert systems; big data analytics; big data analysis; I4.0; bibliometric analysis1. Introduction The fourth Industrial Revolution (I4.0) brought out many disruptive technologies that have substantially transformed...