Research map / Large language models / Language, safety and interpretability
When Truth Is Overridden: Uncovering the Internal Origins of Sycophancy in Large Language Models
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Towards Understanding Sycophancy in Language Models (ICLR 2024 · similarity 0.92)
- When Helpfulness Becomes Sycophancy: Sycophancy is a Boundary Failure Between Social Alignment and Epistemic Integrity in Large Language Models (NeurIPS 2026 · similarity 0.91)
- Stability Regimes for Framing-Sensitive Fine-Tuning in Language Models (NeurIPS 2026 · similarity 0.88)
- From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning (ICML 2024 · similarity 0.87)
- Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs (ICLR 2025 · similarity 0.87)
- LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations (ICLR 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
