Are You Sure You're Sure? Two Confounds in a Sycophancy Benchmark

arXiv:2609.32867 · cs.CL · Submitted 2026-09-26 · Read on arXiv

cs.CL

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Sycophancy — 27× in this paper · explained in 4 episodes
• Benchmark — 25× in this paper · explained in 2 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Quantization — 6× in this paper · explained in 12 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Robustness — 2× in this paper · explained in 5 episodes
• Scaffolding — 2× in this paper · explained in 3 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Activation Patching — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Entanglement — 1× in this paper · explained in 3 episodes
• Human-in-the-Loop — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Measuring Sycophancy of Language Models in Multi-turn Dialogues
• BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs
• Are You Sure? Challenging LLMs Leads to Performance Drops in The FlipFlop Experiment
• PENDULUM: A Benchmark for Assessing Sycophancy in Multimodal Large Language Models
• Ask don't tell: Reducing sycophancy in large language models
• Safety Under Scaffolding: How Evaluation Conditions Shape Measured Safety
• Sycophancy Claims about Language Models: The Missing Human-in-the-Loop
• Qwen2.5 Technical Report
• Qwen3 Technical Report
• The Llama 3 Herd of Models
• Measuring Massive Multitask Language Understanding
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Measuring Mathematical Problem Solving With the MATH Dataset
• Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning

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