---
title: "Who cites Seeing is Believing, but How — 5 citing papers"
description: "5 papers of the Elamur Research library cite «Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in…"
canonical: "https://research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Seeing is Believing, but How Much? A…](https://md.research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/) / cited by

# Who cites «Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models»

5 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models»](https://md.research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/)

1. **[Thinking Out Loud: Do Reasoning Models Know When They're Right?](https://md.research.elamur.ai/free/en/papers/zeng-2025-thinking-out-loud-do-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.*2025 · 9 citations*
2. **[Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://md.research.elamur.ai/free/en/papers/ulmer-2026-anthropomimetic-uncertainty-what-verbalized-uncertainty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.*2026 · 4 citations*
3. **[The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use Agents](https://md.research.elamur.ai/free/en/papers/xuan-2026-confidence-dichotomy-analyzing-mitigating-miscalibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.*2026 · 2 citations*
4. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*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/xuan-2025-seeing-is-believing-but-how/) — Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models