This paper investigates the in-context learning abilities of the Whisper...
Multi-Label Image Recognition (MLIR) is a challenging task that aims to
...
The disease is a core concept in the medical field, and the task of
norm...
The NLI4CT task aims to entail hypotheses based on Clinical Trial Report...
The purpose of write-missing diagnosis detection is to find diseases tha...
Batch Normalization (BN) is a core and prevalent technique in accelerati...
The accurate protein-ligand binding affinity prediction is essential in ...
The table-based fact verification task has recently gained widespread
at...
Despite the success of deep learning methods in medical image segmentati...
Potential Drug-Drug Interaction(DDI) occurring while treating complex or...
Estimation of the information content in a neural network model can be
p...
We convert the Chinese medical text attributes extraction task into a
se...
Text classification is one of the most important and fundamental tasks i...
Compared to sequential learning models, graph-based neural networks exhi...
External knowledge is often useful for natural language understanding ta...
Deep learning methods have achieved promising performance in many areas,...
Learning from corpus and learning from supervised NLP tasks both give us...
Despite the great success of word embedding, sentence embedding remains ...
Reading and understanding text is one important component in computer ai...
In this work, we investigated the feasibility of applying deep learning
...
This article describes the final solution of team monkeytyping, who fini...
In this paper, we present a probabilistic framework for goal-driven spok...
Recently, the deep-belief-networks (DBN) based voice activity detection ...