LLMs have shown impressive capabilities in reasoning tasks like Chain-of-Thought (CoT), enhancing accuracy and interpretability in complex problem-solving. While researchers are extending these ...

Reinforcement Learning from Verifiable Rewards (RLVR) has recently emerged as a promising method for enhancing reasoning abilities in language models without direct supervision. This approach has ...

Reinforcement Learning from Verifiable Rewards (RLVR) has recently emerged as a promising method for enhancing reasoning abilities in language models without direct supervision. This approach has ...

Visual Studio Code (VSCode) is a powerful, free source-code editor that makes it easy to write and run Python code. This guide will walk you through setting up VSCode for Python development, step by ...

Recent advancements in AI scaling laws have shifted from merely increasing model size and training data to optimizing inference-time computation. This approach, exemplified by models like OpenAI o1 ...

Supervised fine-tuning (SFT) is the standard training paradigm for large language models (LLMs) and graphic user interface (GUI) agents. However, SFT demands high-quality labeled datasets, resulting ...

Time series analysis faces significant hurdles in data availability, quality, and diversity, critical factors in developing effective foundation models. Real-world datasets often fall short due to ...

3D self-supervised learning (SSL) has faced persistent challenges in developing semantically meaningful point representations suitable for diverse applications with minimal supervision. Despite ...

Autoregressive visual generation models have emerged as a groundbreaking approach to image synthesis, drawing inspiration from language model token prediction mechanisms. These innovative models ...

Monocular depth estimation involves predicting scene depth from a single RGB image—a fundamental task in computer vision with wide-ranging applications, including augmented reality, robotics, and 3D ...

Developing therapeutics continues to be an inherently costly and challenging endeavor, characterized by high failure rates and prolonged development timelines. The traditional drug discovery process ...

The rapid advancements in search engine technologies integrated with large language models (LLMs) have predominantly favored proprietary solutions such as Google’s GPT-4o Search Preview and Perplexity ...