Due to the unbalanced training data distribution, the language ability o...
Current captioning approaches tend to generate correct but "generic"
des...
The paradigm of pre-training followed by fine-tuning on downstream tasks...
Neural machine translation has achieved promising results on many transl...
Large language models (LLMs) have demonstrated remarkable potential in
h...
Augmenting the base neural model with a token-level symbolic datastore i...
Traditional multilingual neural machine translation (MNMT) uses a single...
kNN-MT presents a new paradigm for domain adaptation by building an exte...
In the intersection of molecular science and deep learning, tasks like
v...
Previous domain adaptation research usually neglect the diversity in
tra...
Catastrophic forgetting in continual learning is a common destructive
ph...