Group 1 - The market experienced fluctuations with the ChiNext index leading the decline, while sectors such as pork, innovative drugs, banks, and CROs saw gains, and sectors like gold, glyphosate, controllable nuclear fusion, humanoid robots, environmental equipment, and consumer electronics faced losses [1] - CITIC Securities highlighted that low-valued embodied intelligent application targets and dividend assets continue to attract market interest, suggesting a focus on "AI + robotics" investment opportunities beyond humanoid robots [2] - CICC emphasized that multi-modal reasoning is crucial for enhancing intelligent driving capabilities, with significant advancements expected in the algorithms of leading smart driving companies [2] Group 2 - Huatai Securities pointed out that core assets like A50 and major financial sectors are likely to shift from resilience revaluation to growth revaluation, showing strong fundamentals during the real estate investment cycle adjustment [3] - A50 non-financial ROE is expected to stabilize and recover ahead of the overall non-financial sector, driven by cost improvements and shareholder returns [3] - The current valuation of these companies reflects a higher implied cost of equity than the market average, indicating potential for a significant reduction in risk premium if investors reassess the overlooked growth resilience [3]

文 / 于钟海 , 魏鹳霏 , 肖楷 , 赵丽萍 中金研究 以MiniMax V-Triune新框架成果为例，推理感知统一框架在可拓展性、泛化性初步验证。 V-Triune以三层组件架构实现视觉推理和感知任务统一至强化学 习框架：1）多模态样本数据格式化；2）验证器奖励计算，采用异步客户端-服务器架构，奖励计算和主训练循环解耦；3）数据源级指标监控，便于溯源 和提升稳定性。结合动态IoU奖励机制、冻结ViT参数等工程优化，Orsta系列模型（32B参数）在MEGA-Bench Core基准测试中实现了最高14.1%的性能提 升。 多模态推理助力智能驾驶能力升阶。 在智能驾驶场景，多模态推理是增强道路交通标志识别判断能力、提升复杂场景泛化性的重要途径，正成为头部智 能驾驶企业算法演进的重点。2025年5月30日，蔚来世界模型NVM首个版本正式开启推送，具备全量理解、想象重构和推理能力，能够对实时环境多模信 息进行理解和推演，在选择最优ETC车道通行、停车场自主寻路等场景的性能提升显著。此外，理想自研的VLA大模型亦具备思维链推理能力，以多模态 推理模拟人类驾驶员的思维运作方式。 图表1：MiniMax多模态RL ...