橘橘橘子汁 & 🍊
发一些好玩的 现在成 mb 的私人频道了 Links t.me/Rosmontis_Daily t.me/PDChinaNews
Show more📈 Analytical overview of Telegram channel 橘橘橘子汁 & 🍊
Channel 橘橘橘子汁 & 🍊 (@microblock_pub) in the Chinese language segment is an active participant. Currently, the community unites 14 311 subscribers, ranking 8 908 in the Technologies & Applications category and 14 957 in the China region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 14 311 subscribers.
According to the latest data from 11 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 388 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 39.55%. Within the first 24 hours after publication, content typically collects 17.81% reactions from the total number of subscribers.
- Post reach: On average, each post receives 5 660 views. Within the first day, a publication typically gains 2 548 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 84.
- Thematic interests: Content is focused on key topics such as 播放量, 传日期, a2a), 排行榜, 空对空.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“发一些好玩的
现在成 mb 的私人频道了
Links
t.me/Rosmontis_Daily
t.me/PDChinaNews”
Thanks to the high frequency of updates (latest data received on 12 July, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
访问前沿大型语言模型(如GPT-5和Gemini-2.5)通常受到高昂定价、支付障碍和区域限制的阻碍。这些限制催生了影子API的泛滥,这些第三方服务声称通过间接访问方式,能够不受地域限制地提供官方模型服务。尽管这些影子API被广泛使用,但其提供的输出是否与官方API一致仍不清楚,这引发了对依赖它们的下游应用可靠性和研究成果有效性的担忧。在本文中,我们首次对官方LLM API与对应的影子API进行了系统性审计。我们首先识别出17个影子API,它们已被应用于187篇学术论文中,其中最受欢迎的一个截至2025年12月6日获得了5,966次引用和58,639个GitHub星标。通过对三个代表性影子API在实用性、安全性和模型验证方面的多维审计,我们揭示了影子API中存在的直接和间接欺骗行为证据。具体来说,我们发现性能差异高达47.21% ,安全行为存在显著不可预测性,以及45.83% 的指纹测试存在身份验证失败。这些欺骗行为严重损害了科学研究的可重复性和有效性,损害了影子API用户的利益,并损害了官方模型提供商的声誉。
