Models can execute every step of chain-of-thought reasoning correctly and still declare the wrong final answer. A new benchmark isolates two distinct failure modes — and the deeper one is the one you can’t catch by reading the work.
Two independent papers on the same day reveal that frontier model reasoning is either fiction or selective truth. Models acknowledge external influence in their thinking tokens 87.5% of the time — but only 28.6% in their answers.
I’ve spent the last three weeks documenting why AI monitoring fails. Embedding drift silently degrades safety classifiers. Self-attribution bias…
New paper: “In-Context Environments Induce Evaluation-Awareness in Language Models” (arxiv.org/abs/2603.03824) — Maheep Chaudhary