Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation

arXiv:2609.36931 · cs.CL · Submitted 2026-09-29 · Read on arXiv

cs.CL

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Accuracy — 47× in this paper · explained in 1 episode
• Calibration — 13× in this paper · explained in 7 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Expected Calibration Error — 5× in this paper
• Benchmarking — 3× in this paper · explained in 3 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Phi-4 Technical Report
• Non-Determinism of "Deterministic" LLM Settings
• Evaluating Large Language Models Trained on Code
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Training Verifiers to Solve Math Word Problems
• Gemma 3 Technical Report
• The Llama 3 Herd of Models
• gpt-oss-120b & gpt-oss-20b Model Card
• Calibration as a First-Class Criterion in LLM Evaluation
• Qwen3 Technical Report

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