Abstract We propose an Explicit Conditional Multimodal Variational Auto-Encoder
(ECMVAE) for audio-visual segmentation (AVS), aiming to segment sound sources in the …

As the number of AI systems keeps growing, it is fundamental to implement and develop
efficient control mechanisms to ensure the safe and proper functioning of machine learning …

Conversational emotion recognition is a crucial research topic in human-computer
interactions. Due to the heavy annotation cost and inevitable label ambiguity, collecting …

Multimodal Sentiment Analysis (MSA) is a challenging research area that studies sentiment
expressed from multiple heterogeneous modalities. Given those pre-trained language …

Assessing the quality of natural language generation (NLG) systems through human
annotation is very expensive. Additionally, human annotation campaigns are time …

When working with textual data, a natural application of disentangled representations is fair
classification where the goal is to make predictions without being biased (or influenced) by …

A new metric\texttt {BaryScore} to evaluate text generation based on deep contextualized
embeddings eg, BERT, Roberta, ELMo) is introduced. This metric is motivated by a new …

Abstract In Machine Learning, a benchmark refers to an ensemble of datasets associated
with one or multiple metrics together with a way to aggregate different systems …

In recent years, multimodal sentiment analysis (MSA) has attracted more and more interest,
which aims to predict the sentiment polarity expressed in a video. Existing methods typically …

Visual emotion analysis (VEA) aiming to detect the emotions behind images, has gained
increasing attention with the development of online social media. Recent studies in prompt …