Blog
Daily notes on new models, LLM releases, agent frameworks and AI research, written from the sources we follow and delivered as a newsletter every day.
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LLMs1 min read
A new framework combines structured reasoning and distance-aware calibration to enhance confidence estimation in LLMs, evaluated on diverse datasets.
From arXiv cs.CL
Agents1 min read
LangSmith’s new LLM-as-a-Judge evaluators incorporate self-improvement through stored human corrections, reducing prompt engineering and enabling adaptive alignment with user preferences. This streamlines evaluation for generative LLM applications.
From LangChain blog
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.
