│ │ ├── nuscenes_infos_train.pkl
助力全国统一大市场建设。保障市场公平竞争。审结涉经营主体行政许可、行政协议类案件2.5万件，同比增长4.7%，促推破除地方保护和市场分割。助力整治“内卷式”竞争，认定构成垄断案件27件。促进市场要素高效配置。审结破产案件3.2万件，同比增长5.1%，助力1481家企业重获新生，推动2.9万家“僵尸企业”依法出清，盘活存量资产1.1万亿元。河北、辽宁、江西、山东、河南、西藏、宁夏、新疆等地在省级层面健全破产工作行政与司法联动机制，南京、宁波、合肥、佛山、成都、西安等地深化破产事务中心建设，实现破产审判效能、企业重整效率和资源配置效益“三提升”。维护资本市场秩序。会同中国证监会出台意见，协同推动资本市场高质量发展。审结涉证券、期货、基金等案件2.5万件，同比增长53.6%。严惩欺诈发行、财务造假等违法犯罪，保护投资者合法权益。某上市公司虚增营收11亿元，法院依法判处实际控制人有期徒刑六年，判令公司赔偿投资者损失7.7亿元。
。新收录的资料对此有专业解读
Several open-source multimodal language models have adapted their methodologies accordingly, e.g., Gemma3 (opens in new tab) uses pan-and-scan and NVILA (opens in new tab) uses Dynamic S2. However, their trade-offs are difficult to understand across different datasets and hyperparameters. To this end, we conducted an ablation study of several techniques. We trained a smaller 5 billion parameter Phi-4 based proxy model on a dataset of 10 million image-text pairs, primarily composed of computer-use and GUI grounding data. We compared with Dynamic S2, which resizes images to a rectangular resolution that minimizes distortion while admitting a tiling by 384×384 squares; Multi-crop, which splits the image into potentially overlapping 384×384 squares and concatenates their encoded features on the token dimension; Multi-crop with S2, which broadens the receptive field by cropping into 1536×1536 squares before applying S2; and Dynamic resolution using the Naflex variant of SigLIP-2, a natively dynamic-resolution encoder with adjustable patch counts.
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