arXiv: cs.AI preprintsInternational11 November 2026
FinCutBench: A Continually Updated Benchmark for Measuring the Temporal Boundaries of LLM Financial Knowledge
This is an official announcement record
Firsthand records what arXiv: cs.AI preprints announced and links to the original. The wording below is theirs, not ours.
arXiv:2611.11588v2 Announce Type: replace Abstract: In financial backtesting and other point-in-time tasks, external inputs can be restricted by date, but model parameters may retain financial facts disclosed later, introducing parametric look-ahead bias. We introduce FinCutBench, a continually updated monthly financial knowledge benchmark for measuring how far a fixed model's financial knowledge extends over calendar time. The current dataset contains 9,000 Chinese and English four-option multiple-choice questions from January 2023 to September 2026, covering Chinese and U.S. markets and four
Read the official announcement
Opens arxiv.org
More from arXiv: cs.AI preprints
- Auditable Human-Agent Teams for Autonomous X-ray Experimentation11 November 2026
- EarthRecord: From Pixels to Land Change with Multimodal Agents over Four Decades of Satellite Imagery11 November 2026
- Train on prefill, monitor at decode: Using sparse autoencoders for topic monitoring11 November 2026
- LandslideFM: A Foundation Model Towards Unified Landslide Perception and Understanding11 November 2026
- Tracing Psychometric Inference in Large Language Models11 November 2026
This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.