English

BAR Conjecture: the Feasibility of Inference Budget-Constrained LLM Services with Authenticity and Reasoning

Machine Learning 2025-08-05 v2

Abstract

When designing LLM services, practitioners care about three key properties: inference-time budget, factual authenticity, and reasoning capacity. However, our analysis shows that no model can simultaneously optimize for all three. We formally prove this trade-off and propose a principled framework named The BAR Theorem for LLM-application design.

Keywords

Cite

@article{arxiv.2507.23170,
  title  = {BAR Conjecture: the Feasibility of Inference Budget-Constrained LLM Services with Authenticity and Reasoning},
  author = {Jinan Zhou and Rajat Ghosh and Vaishnavi Bhargava and Debojyoti Dutta and Aryan Singhal},
  journal= {arXiv preprint arXiv:2507.23170},
  year   = {2025}
}