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Canada-0-LOGISTICS 公司名錄
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公司新聞:
- IDEA | Jian Guo
研究构建含19 2K样本的ChartPoint-SFT-62k数据集，集成逐步推理、关键位置标注及可视化修正，基于Qwen2-VL微调出ChartPointQ2 Q2 5模型。 在ChartQA和ChartBench基准测试中，模型较现有技术显著提升，尤其在文本标注稀疏场景下实现5 04%的性能增益，为复杂图表推理
- ICCV 2025 Open Access Repository
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
- ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
- ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
- Fugu-MT 論文翻訳 (概要): ChartPoint: Guiding MLLMs with . . .
さらに、ステップバイステップのCoT、バウンディングボックス、再レンダリングされた視覚化を備えた19 2Kの高品質チャートサンプルを含むデータセットであるChartPoint-SFT-62kを構築するための自動パイプラインも導入する。
- ChartPoint: Guiding MLLMs with Grounding Reflection for . . .
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
- IDEA | Jian Guo
研究构建含19 2K样本的ChartPoint-SFT-62k数据集，集成逐步推理、关键位置标注及可视化修正，基于Qwen2-VL微调出ChartPointQ2 Q2 5模型。 在ChartQA和ChartBench基准测试中，模型较现有技术显著提升，尤其在文本标注稀疏场景下实现5 04%的性能增益，为复杂图表推理
- 深度对比: SFT、ReFT、RHLF、RLAIF、DPO、PPO - 微软 . . .
1 ReFT（Reinforced Fine-Tuning，强化微调）：这是SFT和PPO（近端策略优化）的结合。 在第一阶段，模型通过SFT在有标注的数据上进行训练，建立基本的语言理解和生成能力。 第二阶段，引入PPO算法，对模型进行强化学习优化。
- ICCV Poster ChartPoint: Guiding MLLMs with Grounding Reflection for . . .
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
- ChartPoint: Guiding MLLMs with Grounding Reflection for Chart Reasoning
We further introduce an automated pipeline to construct ChartPoint-SFT-62k, a dataset featuring 19 2K high-quality chart samples with step-by-step CoT, bounding box, and re-rendered visualizations
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