Large language models (LLMs) have transformed natural language processing (NLP) by demonstrating the effectiveness of increasing the number of parameters and training data for various reasoning tasks. One successful method, chain-of-thought (CoT) prompting, helps language models solve complex problems by breaking them into intermediate steps written as text before giving the final answer, focusing on… →
INTRODUCTION: Although the prognosis of Langerhans cell histiocytosis (LCH) is excellent, the high recurrence rate and permanent consequences, such as central diabetes insipidus and LCH-associated neurodegenerative diseases, remain to be resolved. Based on previous reports that patients with high-risk multisystem LCH show elevated levels of inflammatory molecules, we hypothesised that dexamethasone would more effectively suppress… →
INTRODUCTION: Participation in bowel cancer screening is lower in regions where there is high ethnic diversity and/or socioeconomic deprivation. Interventions, such as text message reminders and patient navigation (PN), have the potential to increase participation in these areas. As such, there is interest in the comparative effectiveness of these interventions to increase bowel cancer screening… →
Language Models (LMs) have significantly advanced complex NLP tasks through sophisticated prompting techniques and multi-stage pipelines. However, designing these LM Programs relies heavily on manual “prompt engineering,” a time-consuming process of crafting lengthy prompts through trial and error. This approach faces challenges, particularly in multi-stage LM programs where gold labels or evaluation metrics for individual… →
Large Language Models (LLMs) are the so far greatest advancement in the field of Artificial Intelligence (AI). However, since these models are trained on extensive and varied corpora, they can unintentionally contain harmful information. This can sometimes also include instructions on how to make biological pathogens. It is necessary to eliminate every instance of this… →
AI holds significant potential to revolutionize healthcare by predicting disease progression using vast health records, thus enabling personalized care. Understanding multi-morbidity—clusters of chronic and acute conditions influenced by lifestyle, genetics, and socioeconomic factors—is crucial for tailored healthcare and preventive measures. Despite existing prediction algorithms for specific diseases, there is a gap in comprehensive models that… →
The concept of Instruction Pre-Training (InstructPT) is a collaborative effort between Microsoft Research and Tsinghua University. This method leverages supervised multitask learning to pre-train language models. Traditional pre-training methods, called Vanilla Pre-Training, rely on unsupervised learning from raw corpora. However, Instruction Pre-Training augments this approach by incorporating instruction-response pairs generated from raw text, enhancing the… →
Sound is indispensable for enriching human experiences, enhancing communication, and adding emotional depth to media. While AI has made significant progress in various domains, incorporating sound in video-generating models with the same sophistication and nuance as human-created content remains challenging. Producing scores for these silent videos is a significant next step in making generated films.… →
In recent research, the Institute for Natural Language Processing (IMS) at the University of Stuttgart, Germany, has introduced ToucanTTS, significantly advancing the field of text-to-speech (TTS) technology. With support for speech synthesis in more than 7,000 languages, this new toolset is capable of completely transforming the field of multilingual TTS systems. ToucanTTS is an advanced… →
Natural language processing has greatly improved language model finetuning. This process involves refining AI models to perform specific tasks more effectively by training them on extensive datasets. However, creating these large, diverse datasets is complex and expensive, often requiring substantial human input. This challenge has created a gap between academic research, which typically uses smaller… →