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Research2 min read
Research evaluated six LLMs across draft-verify-revise pipelines to assess their ability to resolve deictic ambiguity. Results showed that GPT-5.2 and Gemini 3 Pro achieved near-perfect accuracy with sufficient reasoning effort, highlighting the importance of context management in these systems.
From arXiv cs.AI
LLMs1 min read
Introducing Hy4 Preview New open weight text input (no vision) LLM from Chinese company Tencent today: 770B total parameters, 49B active parameters, 1M token context window, 1.56TB on Hugging Face. This is a big size increase from their ...
From Simon Willison on LLMs
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: .
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.
