Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation 事件

Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation arXiv:2605.04135v2 Announce Type: replace-cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequentially different, question: what older, cheaper, less-elicited models could do months or years earlier (a 2026 paper evaluating GPT-3.5 or GPT-4 zero-shot, say, against a frontier of reasoning-capable