Human-robot collaboration focuses on developing intelligent systems working alongside humans in dynamic environments. Researchers aim to build robots capable of understanding and executing natural ...

Competitive programming has long served as a benchmark for assessing problem-solving and coding skills. These challenges require advanced computational thinking, efficient algorithms, and precise ...

Yann LeCun, Chief AI Scientist at Meta and one of the pioneers of modern AI, recently argued that autoregressive Large Language Models (LLMs) are fundamentally flawed. According to him, the ...

Mathematical reasoning remains a difficult area for artificial intelligence (AI) due to the complexity of problem-solving and the need for structured, logical thinking. While large language models ...

Text-to-speech (TTS) technology has made significant strides in recent years, but challenges remain in creating natural, expressive, and high-fidelity speech synthesis. Many TTS systems struggle to ...

Planning: Generates an outline for the essay. Research: Retrieves relevant documents using Tavily. Writing: Uses the research to generate the first draft. Reflection: Critiques the draft for ...

Real-time speech translation presents a complex challenge, requiring seamless integration of speech recognition, machine translation, and text-to-speech synthesis. Traditional cascaded approaches ...

Time series forecasting presents a fundamental challenge due to its intrinsic non-determinism, making it difficult to predict future values accurately. Traditional methods generally employ point ...

The International Mathematical Olympiad (IMO) is a globally recognized competition that challenges high school students with complex mathematical problems. Among its four categories, geometry stands ...

Large language models (LLMs) are the foundation for multi-agent systems, allowing multiple AI agents to collaborate, communicate, and solve problems. These agents use LLMs to understand tasks, ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...

As deep learning models continue to grow, the quantization of machine learning models becomes essential, and the need for effective compression techniques has become increasingly relevant. Low-bit ...