Pre Trained Language

Pre-trained language models (PLMs) are revolutionizing natural language processing by providing powerful, general-purpose representations of text. Current research focuses on improving PLM efficiency (e.g., through model compression and parameter-efficient tuning), addressing biases and limitations in factual knowledge and reasoning capabilities, and enhancing their performance on specific downstream tasks like question answering and text generation via techniques such as instruction tuning and prompt engineering. These advancements are significantly impacting various fields, enabling more efficient and effective applications in areas ranging from hate speech detection to knowledge graph completion and biomedical document retrieval.