Archive · · Apr 2026 – Apr 2026 · Updated 00:06 UTC
Archive Every processed story in chronological order, with the newest coverage first. Filter by tag, source, or score to drill in.
Total · all-time 10
Avg score 6.1 ▲ 0.4 vs all tags
Stories / month Peak 7
Jun 25 Sep 25 Dec 25 Mar 26 Jun 26
Filters · 2 tag: multimodal × author: Aeroi ×
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All categories 1 New Models & Releases 0 Agent Frameworks & Tools 0 Agentic Coding 0 Research Papers 0 Open Source 0 Industry & Business 0 Infrastructure & MLOps 0 Tutorials & How-To 0 Regulation & Safety 0 Applications & Use Cases 1 Opinion & Analysis 0 Community & Events 0 Source kind
Any source kind 1 Primary (vendor) 0 Community (HN, Reddit, X) 1 Research (arXiv) 0 Repos (GitHub) 0 Top authors
AI Engineer 1 Aeroi 1 Aris Tsakpinis 1 Muhammad Yasir 1 Peiyang Xu, Bangzheng Li, Sijia Liu 1 Xuanle Zhao, Qiushi Sun, Jingyu Xiao 1 Yan Li, Zezi Zeng, Yifan Yang 1 billy42 1 Top tags
#benchmarks · 2 #field-operations · 1 #industrial-applications · 1 #multimodal · 1 #open-source · 1 #physical-agents · 1 #physical-world-agents · 1 #agent-framework · 1 #tool-use · 1
Co-occurring tags
+#benchmarks · 1 +#field-operations · 1 +#open-source · 1 +#physical-agents · 1
1 story· Showing 1–1 · Page 1 of 1
W17 1 story · Apr 20–26
Practitioners building AI agents for industrial or field environments now have a domain-specific open benchmark to evaluate and compare performance on real-world physical-world tasks, rather than relying on general-purpose evals that miss industry-specific skills.