arXiv (All)
open access
On the Position Bias of Large Language Models: A Comprehensive Study
Recent studies have shown that position bias remains a critical vulnerability in large language models (LLMs), undermining both the integrity of multiple-choice evaluations and the reliability of retrieval-augmented generation. However, existing understanding of this phenomenon is largely derived fr
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Monocultural Biases: Correlated biases in large language models lead to unequal systemic exclusion rates in hiring#1036852
- Apparent Psychological Profiles of Large Language Models are Largely a Measurement Artifact#290636
- The World as Viewed by 136 Countries: An Open, Curated, Annotated, and Multilingual Dataset of 118 Million State Media Articles#1389936
- Evaluating Criterion-Conditioned Behaviour of Large Language Models in Content Moderation#926695
- Large Language Models Substantially Compress Well-Being Inequality but Largely Preserve Its Socioeconomic Structure#1117767
Record · ID 1386776
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive