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Found 27 papers, 14 papers with code
A Cancel Culture Corpus through the Lens of Natural Language Processing
Cancel Culture as an Internet phenomenon has been previously explored from a social and legal science perspective.
SeqAttack: On Adversarial Attacks for Named Entity Recognition
Named Entity Recognition is a fundamental task in information extraction and is an essential element for various Natural Language Processing pipelines.
Finding the Law: Enhancing Statutory Article Retrieval via Graph Neural Networks
Statutory article retrieval (SAR), the task of retrieving statute law articles relevant to a legal question, is a promising application of legal text processing.
Clustering individuals based on multivariate EMA time-series data
In the field of psychopathology, Ecological Momentary Assessment (EMA) methodological advancements have offered new opportunities to collect time-intensive, repeated and intra-individual measurements.
Imagination is All You Need! Curved Contrastive Learning for Abstract Sequence Modeling Utilized on Long Short-Term Dialogue Planning
Motivated by the entailment property of multi-turn dialogues through contrastive learning sentence embeddings, we introduce a novel technique, Curved Contrastive Learning (CCL), for generating semantically meaningful and conversational graph curved utterance embeddings that can be compared using cosine similarity.
Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data
Interestingly, it is observed that in one of the two real-world datasets, knowledge distillation method achieves improved AUC scores (mean relative change of +17\% compared to personalized) showing how it can benefit EMA data classification and performance.
A Statutory Article Retrieval Dataset in French
Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question.
Ranked #1 on
Information Retrieval
on BSARD
Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer
As a result, one should not expect that for a target language $L_1$ there is a single language $L_2$ that is the best choice for any NLP task (for instance, for Bulgarian, the best source language is French on POS tagging, Russian on NER and Thai on NLI).
Can we detect harmony in artistic compositions? A machine learning approach
Harmony in visual compositions is a concept that cannot be defined or easily expressed mathematically, even by humans.
Evaluating Bias In Dutch Word Embeddings
Recent research in Natural Language Processing has revealed that word embeddings can encode social biases present in the training data which can affect minorities in real world applications.
"Thy algorithm shalt not bear false witness": An Evaluation of Multiclass Debiasing Methods on Word Embeddings
Specifically, in the natural language processing domain, it has been shown that social biases persist in word embeddings and are thus in danger of amplifying these biases when used.
Adapting End-to-End Speech Recognition for Readable Subtitles
The experiments show that with limited data far less than needed for training a model from scratch, we can adapt a Transformer-based ASR model to incorporate both transcription and compression capabilities.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Low-Latency Sequence-to-Sequence Speech Recognition and Translation by Partial Hypothesis Selection
On How2 English-Portuguese speech translation, we reduce latency to 0. 7 second (-84% rel.)
Sequence-To-Sequence Speech Recognition
speech-recognition
+1
Hybrid Tiled Convolutional Neural Networks for Text Sentiment Classification
The tiled convolutional neural network (tiled CNN) has been applied only to computer vision for learning invariances.
LoGANv2: Conditional Style-Based Logo Generation with Generative Adversarial Networks
Domains such as logo synthesis, in which the data has a high degree of multi-modality, still pose a challenge for generative adversarial networks (GANs).
#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
Inspired by the recent social movement of #MeToo, we are building a chatbot to assist survivors of sexual harassment cases (designed for the city of Maastricht but can easily be extended).
Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction
Time Series forecasting (univariate and multivariate) is a problem of high complexity due the different patterns that have to be detected in the input, ranging from high to low frequencies ones.
Exploring the context of recurrent neural network based conversational agents
Conversational agents have begun to rise both in the academic (in terms of research) and commercial (in terms of applications) world.
Towards Controlled Transformation of Sentiment in Sentences
The autoencoder is tested on how well it is able to change the sentiment of an encoded phrase and it was found that such a task is possible.
LoGAN: Generating Logos with a Generative Adversarial Neural Network Conditioned on color
Yet, conditional generative adversarial networks can be used to generate logos that could help designers in their creative process.
Social Emotion Mining Techniques for Facebook Posts Reaction Prediction
In order to predict the distribution of reactions of a new post, neural network architectures (convolutional and recurrent neural networks) were tested using pretrained word embeddings.
A retrieval-based dialogue system utilizing utterance and context embeddings
Finding semantically rich and computer-understandable representations for textual dialogues, utterances and words is crucial for dialogue systems (or conversational agents), as their performance mostly depends on understanding the context of conversations.
Massive Open Online Courses Temporal Profiling for Dropout Prediction
Massive Open Online Courses (MOOCs) are attracting the attention of people all over the world.
Accumulated Gradient Normalization
This work addresses the instability in asynchronous data parallel optimization.
Bagged Boosted Trees for Classification of Ecological Momentary Assessment Data
Ecological Momentary Assessment (EMA) data is organized in multiple levels (per-subject, per-day, etc.)
AMSOM: Adaptive Moving Self-organizing Map for Clustering and Visualization
Self-Organizing Map (SOM) is a neural network model which is used to obtain a topology-preserving mapping from the (usually high dimensional) input/feature space to an output/map space of fewer dimensions (usually two or three in order to facilitate visualization).
