Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …

A humanized dialogue system is expected to generate empathetic replies, which should be
sensitive to the users' expressed emotion. The task of empathetic dialogue generation is …

Continual learning has become increasingly important as it enables NLP models to
constantly learn and gain knowledge over time. Previous continual learning methods are …

Neural controllable text generation is an important area gaining attention due to its plethora
of applications. Although there is a large body of prior work in controllable text generation …

While vast amounts of personal data are shared daily on public online platforms and used
by companies and analysts to gain valuable insights, privacy concerns are also on the rise …

Paraphrase generation plays an essential role in natural language process (NLP), and it has
many downstream applications. However, training supervised paraphrase models requires …

Existing methods for adapting large language models (LLMs) to new tasks are not suited to
multi-task adaptation because they modify all the model weights--causing destructive …

Continual learning has gained increasing importance as it facilitates the acquisition and
refinement of scalable knowledge and skills in language models. However, existing …

Large Language Models (LLMs) are trained on corpora disproportionally weighted in favor
of Standard American English. As a result, speakers of other dialects experience …

The field of NLP has made substantial progress in building meaning representations.
However, an important aspect of linguistic meaning, social meaning, has been largely …