Фото: Borut Zivulovic / Reuters
Our primary finding is that dynamic resolution vision encoders perform the best and especially well on high-resolution data. It is particularly interesting to compare dynamic resolution with 2048 vs 3600 maximum tokens: the latter roughly corresponds to native HD 720p resolution and enjoys a substantial boost on high-resolution benchmarks, particularly ScreenSpot-Pro. Reinforcing the high-resolution trend, we find that multi-crop with S2 outperforms standard multi-crop despite using fewer visual tokens (i.e., fewer crops overall). The dynamic resolution technique produces the most tokens on average; due to their tiling subroutine, S2-based methods are constrained by the original image resolution and often only use about half the maximum tokens. From these experiments we choose the SigLIP-2 Naflex variant as our vision encoder.
，更多细节参见爱思助手
Okay I’m not reading that.
“龙虾”（OpenClaw）开源AI项目热度攀升，多家互联网厂商正式发布AI智能助手，市场对AI商业化落地预期显著升温，头部互联网云厂商等指数核心成分股有望受益于算力需求激增。当前恒生科技PE-TTM为21倍，处于历史13.1%的分位数，显著低于科创50指数（165倍）与纳斯达克100指数（33倍）。具备较强安全边际与配置吸引力。