Table 5:Performancecomparison of models trained on different datasets. The ReachQA and CharXiv scores refer to Reas. splits here. ModelsAvg.ReachQACharXivMathVistaMath-V Base Model16.396.5017.2032.409.44 + ChartBench17.067.3017.0033.6010.33
首先,该字符串 s 可以从模型 fθ 中提取出来,也就是说,该模型能够生成包含字符串 s 的文本序列,模型记住了s。 其次,字符串 s 在训练数据 X 中最多出现在 k 个示例中,即 s 在训练数据 X 中出现的次数不超过 k 次。这里通过计算训练数据 X 中包含字符串 s 的样本数量来判断,表示为 |{x ∈ X : s...
With the deepening of research on Large Language Models (LLMs), significant progress has been made in recent years on the development of Large Multimodal Models (LMMs), which are gradually moving toward Artificial General Intelligence. This paper aims to summarize the recent progress from LLMs to...
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(LLMs) to rephrase the search query and extend the aesthetic expectations can make up for this shortcoming. Based on the above findings, we propose a preference-based reinforcement learning method that fine-tunes the vision models to distill the knowledge from both LLMs reasoning and the ...
microsoft/lmops - 用于通过大型语言模型(LLMs)和多模态大型语言模型(MLLMs)实现人工智能能力的通用技术。 llm-workflow-engine/llm-workflow-engine - 适用于大型语言模型(核心包)的Power CLI和工作流管理器。 timescale/pgai - 一组用于更轻松地开发使用PostgreSQL的检索增强生成(RAG)、语义搜索和其他人工智能应用...
2.1 How can we use MLLMs for Diffusion Synthesis that Synergizes both sides? 3 DreamLLM 3.1 End-to-End Interleaved generative Pretraining (I-GPT) 3.2 Model Training 4 Experiments and 4.1 Multimodal Comprehension 4.2 Text-Conditional Image Synthesis ...
In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training ...
generating text that is not factually grounded in associated images. The problem makes existing MLLMs untrustworthy and thus impractical in real-world (especially high-stakes) applications. To address the challenge, we present RLHF-V, which enhances MLLM trustworthiness via behavior alignment from ...
In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training ...