The rapid development of Large Language Models (LLMs) has transformed natural language processing (NLP). Proprietary models like GPT-4 and Claude 3 have set high standards in terms of performance but ...

Theory of Mind (ToM) is a foundational element of human social intelligence, enabling individuals to interpret and predict the mental states, intentions, and beliefs of others. This cognitive ability ...

Natural Language processing uses large language models (LLMs) to enable applications such as language translation, sentiment analysis, speech recognition, and text summarization. These models depend ...

Large Language Models (LLMs) and neural architectures have significantly advanced capabilities, particularly in processing longer contexts. These improvements have profound implications for various ...

Reasoning systems such as o1 from OpenAI were recently introduced to solve complex tasks using slow-thinking processes. However, it is clear that large language models have limitations, as they cannot ...

Large Language Models (LLMs) play a vital role in many AI applications, ranging from text summarization to conversational AI. However, evaluating these models effectively remains a significant ...

The robotics and embodied AI field has long struggled with accessibility and efficiency issues. Creating realistic physical simulations requires extensive technical expertise, expensive hardware, and ...

Speech synthesis technology has made notable strides, yet challenges remain in delivering real-time, natural-sounding audio. Common obstacles include latency, pronunciation accuracy, and speaker ...

The evaluation of LLMs in medical tasks has traditionally relied on multiple-choice question benchmarks. However, these benchmarks are limited in scope, often yielding saturated results with repeated ...

Long-context LLMs enable advanced applications such as repository-level code analysis, long-document question-answering, and many-shot in-context learning by supporting extended context windows ...

Reinforcement Learning is now applied in almost every pursuit of science and tech, either as a core methodology or to optimize existing processes and systems. Despite broad adoption even in highly ...

Software development presents numerous challenges, from debugging complex code to navigating legacy systems and adapting to rapidly evolving technologies. These ...