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Found 21 papers, 2 papers with code
Learning to Generate Examples for Semantic Processing Tasks
Experiments in low resource settings show that augmenting the training material with the proposed strategy systematically improves the results on text classification and natural language inference tasks by up to 10% accuracy, outperforming existing DA approaches.
Learning to Solve NLP Tasks in an Incremental Number of Languages
In real scenarios, a multilingual model trained to solve NLP tasks on a set of languages can be required to support new languages over time.
GAN-BERT: Generative Adversarial Learning for Robust Text Classification with a Bunch of Labeled Examples
Recent Transformer-based architectures, e. g., BERT, provide impressive results in many Natural Language Processing tasks.
GASP! Generating Abstracts of Scientific Papers from Abstracts of Cited Papers
In this paper, we dare to introduce the novel, scientifically and philosophically challenging task of Generating Abstracts of Scientific Papers from abstracts of cited papers (GASP) as a text-to-text task to investigate scientific creativity, To foster research in this novel, challenging task, we prepared a dataset by using services where that solve the problem of copyright and, hence, the dataset is public available with its standard split.
Auditing Deep Learning processes through Kernel-based Explanatory Models
While NLP systems become more pervasive, their accountability gains value as a focal point of effort.
Explaining non-linear Classifier Decisions within Kernel-based Deep Architectures
Nonlinear methods such as deep neural networks achieve state-of-the-art performances in several semantic NLP tasks.
Structured Learning for Context-aware Spoken Language Understanding of Robotic Commands
Service robots are expected to operate in specific environments, where the presence of humans plays a key role.
Deep Learning in Semantic Kernel Spaces
Kernel methods enable the direct usage of structured representations of textual data during language learning and inference tasks.
A Language Independent Method for Generating Large Scale Polarity Lexicons
Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts.
HuRIC: a Human Robot Interaction Corpus
Recent years show the development of large scale resources (e. g. FrameNet for the Frame Semantics) that supported the definition of several state-of-the-art approaches in Natural Language Processing.
