---
title: "Who cites Discourse-Driven Evaluation: — 7 citing papers"
description: "7 papers of the Elamur Research library cite «Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document…"
canonical: "https://research.elamur.ai/free/en/papers/zhong-2025-discourse-driven-evaluation-unveiling-factual/cited-by/"
---
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# Who cites «Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization»

7 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization»](https://md.research.elamur.ai/free/en/papers/zhong-2025-discourse-driven-evaluation-unveiling-factual/)

1. **[StrucSum: Graph-Structured Reasoning for Long Document Extractive Summarization with LLMs](https://md.research.elamur.ai/free/en/papers/yuan-2025-strucsum-graph-structured-reasoning-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haohan Yuan, Sukhwa Hong, Haopeng Zhang*2025 · 9 citations*
2. **[Stress Testing Factual Consistency Metrics for Long-Document Summarization](https://md.research.elamur.ai/free/en/papers/mujahid-2026-stress-testing-factual-consistency-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zain Muhammad Mujahid, Dustin Wright, Isabelle Augenstein*2026 · 3 citations*
3. **[Revisiting Faithfulness Annotations for Long-form Summaries](https://md.research.elamur.ai/free/en/papers/zhong-2026-revisiting-faithfulness-annotations-long-form/) [Linguistic Annotation Workshop (LAW)](https://md.research.elamur.ai/free/en/venues/law/)**Yang Zhong, Yang Janet Liu, Diane Litman*2026*

4 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/zhong-2025-discourse-driven-evaluation-unveiling-factual/) — Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization