arXiv — cs.AI preprintsInternational19 October 2026
Poli-Bias: Understanding and Measuring Large Language Model Biases in International Political Conflicts
This is an official announcement record
Firsthand records what arXiv — cs.AI preprints announced and links to the original. The wording below is theirs, not ours.
arXiv:2608.06123v3 Announce Type: replace Abstract: Measuring political bias in large language models (LLMs) remains challenging as it can manifest through subtle differences in framing, argumentation, and legal reasoning that are difficult to capture with a single metric. In this work, we introduce POLI-BIAS, a counterfactual framework for measuring whether LLMs treat legally equivalent conflict scenarios differently depending on the countries involved. POLI-BIAS compares responses to paired prompts in which country identities are systematically swapped across diverse geopolitical relationshi
Read the official announcement
Opens arxiv.org
More from arXiv — cs.AI preprints
- Structured Authority Injection: Persistent Human Control for LLM Agents via Typed MCP Overrides19 October 2026
- Rethinking User Encoders: Routing Diffusion States for Scenario-Adaptive User Representation19 October 2026
- From Events to Reasoning: Hierarchical Rule Composition over Explicit States19 October 2026
- ECHOES: Seeing Beyond the Current Image via Recursive History Compression and Privileged On-Policy Distillation19 October 2026
- Sensitivity Analysis of Decision Rules in an Agent-Based Agro-Ecological Model19 October 2026
This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.