---
title: "Who cites Uncertainty Quantification in LLM — 3 citing papers"
description: "3 papers of the Elamur Research library cite «Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and…"
canonical: "https://research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Uncertainty Quantification in LLM Agents…](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) / cited by

# Who cites «Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities»

3 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities»](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/)

1. **[Structured Uncertainty guided Clarification for LLM Agents](https://md.research.elamur.ai/free/en/papers/suri-2026-structured-uncertainty-guided-clarification-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Manan Suri, Puneet Mathur, Nedim Lipka, et al.*2026 · 4 citations*
2. **[Thesis Proposal: When Does an Agent Know It Is Lost? Confidence Trajectory Analysis for Tool-Using LLMs](https://md.research.elamur.ai/free/en/papers/mao-2026-thesis-proposal-when-does-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenjiang Mao*2026*

1 more paper of our library cites it; it has no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) — Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities