We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed
by consolidating our insights into data, models, and visual representations in the LLaVA …

The proliferation of fake news and fake profiles on social media platforms poses significant
threats to information integrity and societal trust. Traditional detection methods, including …

The needle-in-a-haystack (NIAH) test, which examines the ability to retrieve a piece of
information (the" needle") from long distractor texts (the" haystack"), has been widely …

In this report, we introduce the Qwen2. 5-Coder series, a significant upgrade from its
predecessor, CodeQwen1. 5. This series includes six models: Qwen2. 5-Coder-(0.5 B/1.5 …

The development of video large multimodal models (LMMs) has been hindered by the
difficulty of curating large amounts of high-quality raw data from the web. To address this, we …

Today's most advanced multimodal models remain proprietary. The strongest open-weight
models rely heavily on synthetic data from proprietary VLMs to achieve good performance …

In this report, we present a series of math-specific large language models: Qwen2. 5-Math
and Qwen2. 5-Math-Instruct-1.5 B/7B/72B. The core innovation of the Qwen2. 5 series lies in …

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities
in executing instructions for a variety of single-image tasks. Despite this progress, significant …

Large Language Models (LLMs) have demonstrated remarkable capabilities across various
fields, from natural language understanding to text generation. Compared to non-generative …

Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in
addressing the challenges of Large Language Models (LLMs) without necessitating …