Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

Large language models (LLMs) have shown powerful performance and development
prospect and are widely deployed in the real world. However, LLMs can capture social …

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …

Recent research has shown that large-scale pretrained language models, specifically
transformers, tend to exhibit issues relating to racism, sexism, religion bias, and toxicity in …

There has been a recent wave of work assessing the fairness of machine learning models in
general, and more specifically, on natural language processing (NLP) models built using …

Demographic biases and social stereotypes are common in pretrained language models
(PLMs), and a burgeoning body of literature focuses on removing the unwanted …

Abstract Machine learning presents opportunities for tracking evidence on climate change
adaptation, including text-based methods from natural language processing. In theory, such …

Large Language Models (LLMs) such as ChatGPT, have gained significant attention due to
their impressive natural language processing capabilities. It is crucial to prioritize human …

Several works have proven that finetuning is an applicable approach for debiasing
contextualized word embeddings. Similarly, discrete prompts with semantic meanings have …

Existing bias mitigation methods require social-group-specific word pairs (eg,“man”–
“woman”) for each social attribute (eg, gender), restricting the bias mitigation to only one …