single pass
single pass at Beyond Market Intelligence is a file of 2 stories. The newest of them: “A Clear Signal for Model Uncertainty, No Extra Sampling Needed” and “Transform an Open LLM Into a Fast Classifier by Swapping Its Head”. Building on open-weight reasoning models often leaves you wondering how confident the model actually is in its answer. Swapping a language-modeling head for a classification head turns a small Qwen LLM into a fast, single-pass text classifier. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every single pass story on Beyond Market Intelligence, newest first.
A Clear Signal for Model Uncertainty, No Extra Sampling Needed
Building on open-weight reasoning models often leaves you wondering how confident the model actually is in its answer. The typical fix, multiple sampling rounds, a judge model, or labeled datasets, is expensive and slow. U-Lens changes that. It extracts an uncertainty signal from a single forward pass, no resampling required. The approach combines hidden-state direction analysis with token entropy, and it outperforms multi-pass baselines across several benchmarks. This is practical, label-free, and ready to use.
Transform an Open LLM Into a Fast Classifier by Swapping Its Head
Swapping a language-modeling head for a classification head turns a small Qwen LLM into a fast, single-pass text classifier. That's a practical move, not a theoretical one. It makes open-source models more useful for real tasks without the overhead of full generation. We see this as a natural step toward focused, efficient AI tools. For deeper context on how calibrated models handle high-frequency decisions, our piece "Smart Graph Decisions at Scale" explores that territory. This is about building smarter workflows, not just faster ones.