Large language models (LLMs) have made significant success in various language tasks, but steering their outputs to meet specific properties remains a challenge. Researchers are attempting to solve ...

AI Control assesses the safety of deployment protocols for untrusted AIs through red-teaming exercises involving a protocol designer and an adversary. AI systems, like chatbots with access to tools ...

In recent research, a state-of-the-art technique has been introduced for utilizing Large Language Models (LLMs) to verify RDF (Resource Description Framework) triples, emphasizing the significance of ...

AI safety frameworks have emerged as crucial risk management policies for AI companies developing frontier AI systems. These frameworks aim to address catastrophic risks associated with AI, including ...

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and ...

Stochastic optimization problems involve making decisions in environments with uncertainty. This uncertainty can arise from various sources, such as sensor noise, system disturbances, or unpredictable ...

Language model research has rapidly advanced, focusing on improving how models understand and process language, particularly in specialized fields like finance. Large Language Models (LLMs) have moved ...

With the success of LLMs in various tasks, search engines have begun using generative methods to provide accurate answers with in-line citations to user queries. However, generating reliable and ...

ML models are increasingly used in weather forecasting, offering accurate predictions and reduced computational costs compared to traditional numerical weather prediction (NWP) models. However, ...

Artificial Intelligence (AI) and Machine Learning (ML) have been transformative in numerous fields, but a significant challenge remains in the reproducibility of experiments. Researchers frequently ...

Large Language Models (LLMs) have demonstrated impressive performance in tasks like Natural Language Processing, generation, and text synthesis. However, they still encounter major difficulties in ...

Data-Free Knowledge Distillation (DFKD) methods transfer knowledge from teacher to student models without real data, using synthetic data generation. Non-adversarial approaches employ heuristics to ...