Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation
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Computer Science > Computation and Language
arXiv:2609.36931 (cs)
[Submitted on 29 Sep 2026]
Title:Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation
View a PDF of the paper titled Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation, by Mario Sanz-Guerrero and 3 other authors
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Abstract:Reproducibility is essential for scientific research, yet prior work shows that LLM outputs vary with hardware and batching. We identify an overlooked factor: the hidden injection of the current date into system prompts, which users cannot control and which changes every day. Across 9 recent LLMs and 6 datasets spanning multiple-choice QA (MCQA), math reasoning, code generation, and machine translation, performance varies solely with the current date, with deltas of up to 6% on MCQA, 14% on math reasoning, 7% on code generation, and 2.84 BLEU on machine translation. Model rankings also shift, affecting leaderboards. This date effect exceeds other sources of non-determinism, such as batch size and numerical precision. Standard prompting techniques -- chain-of-thought and few-shot prompting -- do not reduce the sensitivity; chain-of-thought even amplifies it. Our findings underscore the need for careful evaluation protocols to ensure reproducibility and fair comparisons in LLM research.
| Comments: | Accepted to AACL 2026 (Main) |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2609.36931 [cs.CL] |
| (or arXiv:2609.36931v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.36931
arXiv-issued DOI via DataCite (pending registration)
|
Submission history
From: Mario Sanz-Guerrero [view email][v1] Tue, 29 Sep 2026 07:45:31 UTC (713 KB)
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View a PDF of the paper titled Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation, by Mario Sanz-Guerrero and 3 other authors
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