AI/ML Research Digest — Sep 27, 2026

Automated excerpt

Omni‑modal language models consistently favor visual input over audio (a “perceptual” bias) and favor propositional audio content (an “evidence‑form” bias). When agents draw skills from this bank, average benchmark performance improves by 11. 7 % across heterogeneous tasks [8]. Detectable multimodal bias lets us correct models before they affect downstream behavior, and Fisher‑Rao control gives a mathematically sound tool for doing so.

Selected automatically from source text; not independently written or fact-checked. Read the original for full context.