The context-aware emotional reasoning ability of AI systems, especially ...
Existing NTMs with contrastive learning suffer from the sample bias prob...
In Emotion Recognition in Conversations (ERC), the emotions of target
ut...
Pretrained language models have been used in various natural language
pr...
Mental illnesses are one of the most prevalent public health problems
wo...
The exponential growth of biomedical texts such as biomedical literature...
The goal of temporal relation extraction is to infer the temporal relati...
Automated mental health analysis shows great potential for enhancing the...
The performance of abstractive text summarization has been greatly boost...
The information bottleneck (IB) principle has been proven effective in
v...
A key challenge for Emotion Recognition in Conversations (ERC) is to
dis...
Citation graphs can be helpful in generating high-quality summaries of
s...
Different from general documents, it is recognised that the ease with wh...
Recently, neural topic models (NTMs) have been incorporated into pre-tra...
Negation and uncertainty modeling are long-standing tasks in natural lan...
Recently, Transformer model, which has achieved great success in many
ar...
Click-Through Rate (CTR) prediction, is an essential component of online...
Modern text simplification (TS) heavily relies on the availability of go...
To interpret the genetic profile present in a patient sample, it is nece...
We propose a multi-task, probabilistic approach to facilitate distantly
...
Semantic search engines, which integrate the output of text mining (TM)
...
Emotion recognition (ER) is an important task in Natural Language Proces...
Unsupervised relation extraction (URE) extracts relations between named
...
We tackle the nested and overlapping event detection task and propose a ...
Document-level relation extraction is a complex human process that requi...
Inter-sentence relation extraction deals with a number of complex semant...
When constructing models that learn from noisy labels produced by multip...
We present a novel graph-based neural network model for relation extract...