Large Language Models (LLMs) often provide confident answers, raising concerns about their reliability, especially for factual questions. Despite widespread hallucination in LLM-generated content, no established method to assess response trustworthiness exists. Users lack a “trustworthiness score” to determine response reliability without further research or verification. The aim is for LLMs to yield predominantly high trust… →
Multi-layer perceptrons (MLPs), or fully-connected feedforward neural networks, are fundamental in deep learning, serving as default models for approximating nonlinear functions. Despite their importance affirmed by the universal approximation theorem, they possess drawbacks. In applications like transformers, MLPs often monopolize parameters and lack interpretability compared to attention layers. While exploring alternatives, such as the Kolmogorov-Arnold… →
Iterative preference optimization methods have shown efficacy in general instruction tuning tasks but yield limited improvements in reasoning tasks. These methods, utilizing preference optimization, enhance language model alignment with human requirements compared to sole supervised fine-tuning. Offline techniques like DPO are gaining popularity due to their simplicity and efficiency. Recent advancements advocate the iterative application… →
Objective: Although individuals with a family history of alcohol use disorder (AUD) have a superior antidepressant response to ketamine, outcomes in patients with current AUD remain unclear. This study sought to investigate whether intranasal (IN) racemic (R,S)-ketamine had antisuicidal and antidepressant effects in unipolar and bipolar depression and whether comorbid AUD conferred superior antisuicidal outcomes… →
CONCLUSION: The results allow us to consider CA as a possible model of preventive dementia therapy aimed at preventing the progression of cognitive deficits and the development of dementia in people at high risk of developing AD — patients with aMCI. →
CONCLUSIONS: We found little difference in the primary outcome or other secondary outcomes. Advice with additional physiotherapy sessions was found likely to be cost-effective. However, small imprecise incremental costs and quality-adjusted life-years raise questions on whether it is the best use of scarce physiotherapy resources given current service demands. →
This study’s research area is artificial intelligence (AI) and machine learning, specifically focusing on neural networks that can understand binary code. The aim is to automate reverse engineering processes by training AI to understand binaries and provide English descriptions. This is important because binaries can be challenging to comprehend due to their complexity and lack… →
Recent advancements in econometric modeling and hypothesis testing have witnessed a paradigm shift towards integrating machine learning techniques. While strides have been made in estimating econometric models of human behavior, more research still needs to be conducted on effectively generating and rigorously testing these models. Researchers from MIT and Harvard introduce a novel approach to… →
In the age of digital transformation, data is the new gold. Businesses are increasingly reliant on data for strategic decision-making, but this dependency brings significant challenges, particularly when it comes to collaborating with external partners. The traditional methods of sharing data often entail transferring sensitive information to third parties, significantly increasing the risk of security… →