Editing Openai/695ac389-b450-800e-a8b3-540cf70d0ecc (section)

===== - Anthropic’s public research on how language models process information and their internal reasoning helps understand why LLMs hallucinate and what’s needed to build more reliable systems, but it doesn’t frame the “null/abstention” answer option as a standalone innovation in a published blog post or paper. There are Anthropic papers on interpretability and internal concept representation, but nothing currently in their official research archive focused on the abstention mechanism specifically as “null responses.” Anthropic<ref>{{cite web|title=Anthropic|url=https://www.anthropic.com/research/mapping-mind-language-model|publisher=anthropic.com|access-date=2026-01-05}}</ref> =====
* Anthropic’s research into model calibration and understanding when a model “knows what it knows” is related in spirit to this idea, but isn’t always presented as a concrete abstention protocol. Anthropic<ref>{{cite web|title=Anthropic|url=https://www.anthropic.com/research/language-models-mostly-know-what-they-know|publisher=anthropic.com|access-date=2026-01-05}}</ref>