Browsing: ML News
Large language models (LLMs) are expanding in usage, posing new cybersecurity risks. These risks emerge from their core traits: heightened capability in code generation, heightened deployment…
Initially designed for continuous control tasks, Proximal Policy Optimization (PPO) has become widely used in reinforcement learning (RL) applications, including fine-tuning generative models. However, PPO’s effectiveness…
Artificial intelligence (AI) is transforming healthcare, bringing sophisticated computational techniques to bear on challenges ranging from diagnostics to treatment planning. In this dynamic field, large language…
Computer vision, machine learning, and data analysis across many fields have all seen a surge in the usage of synthetic data in the past few years.…
In the ever-evolving field of machine learning, developing models that predict and explain their reasoning is becoming increasingly crucial. As these models grow in complexity, they…
In-context learning (ICL) in large language models (LLMs) utilizes input-output examples to adapt to new tasks without altering the underlying model architecture. This method has transformed…
Traditional methods for training vision-language models (VLMs) often require the centralized aggregation of vast datasets, which raises concerns regarding privacy and scalability. Federated learning offers a…
Time series forecasting is increasingly vital across numerous sectors, such as meteorology, finance, and energy management. Its relevance has grown as organizations aim to predict future…
Graphs are important in representing complex relationships in various domains like social networks, knowledge graphs, and molecular discovery. Alongside topological structure, nodes often possess textual features…
Understanding and reasoning about program execution is a critical skill for developers, often applied during tasks like debugging and code repair. Traditionally, developers simulate code execution…