Archive · · Jun 2026 – Jun 2026 · Updated 23:30 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 12
Avg score 5.8 ▲ 0.0 vs all tags
Stories / month Peak 7
Jun 25 Sep 25 Dec 25 Mar 26 Jun 26
Filters · 2 tag: fine-tuning × author: AI Engineer ×
Category
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) 0 Research (arXiv) 0 Repos (GitHub) 0 Top authors
Weights & Biases 2 Dragos Roua 1 Hugging Face 1 Kirill Vasilevski, Ximing Dong, Benjamin Rombaut 1 Pu Ning, Quan Chen, Kun Tao 1 Ravidu Suien Rammuni Silva, Ahmad Lotfi, Isibor Kennedy Ihianle 1 Yuanjie Lyu, Chengyu Wang, Haonan Zheng 1 Zhaopei Huang, Yanfeng Jia, Jiayi Zhao 1 Top tags
#agent-framework · 10 #mcp · 5 #developer-tools · 5 #tool-use · 4 #prompt-engineering · 3 #developer-culture · 2 #benchmarks · 2 #open-source · 2 #security · 2 #observability · 2 #monitoring · 1 #agentic-coding · 1
Co-occurring tags
+#benchmarks · 1 +#open-source · 1 +#reasoning · 1 +#tool-use · 1
1 story· Showing 1–1 · Page 1 of 1
W24 1 story · Jun 8–14
The results show that targeted RL fine-tuning on high-quality, task-specific data can close — and reverse — a 231-billion-parameter gap in model size, at a training cost under $500, on a real financial reasoning benchmark.