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Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
An arXiv study reveals an academic publication lag where LLM domain benchmarks routinely evaluate outclassed, superseded models.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 25 September 2026
- Collected by OneBench
- 26 Sept 2026, 03:01 UK
Stored source excerpt
arXiv:2605.04135v3 Announce Type: replace-cross Abstract: LLM evaluations in applied domains tend to reflect models that were already outclassed at time of publication. We observe a…
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