--- title: "Who cites On Learning to Summarize with — 55 citing papers" description: "55 papers of the Elamur Research library cite «On Learning to Summarize with Large Language Models as References», found in their…" canonical: "https://research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [On Learning to Summarize with Large Language…](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) / cited by # Who cites «On Learning to Summarize with Large Language Models as References» 55 papers of our library cite it (of the 141,840 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «On Learning to Summarize with Large Language Models as References»](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) 1. **[Bridging Cognition and Affect: Emotion-Aware Opinion Summarization using LLMs](https://md.research.elamur.ai/free/en/papers/attri-2026-bridging-cognition-affect-emotion-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arnav Attri, Anuj Attri*2026* 2. **[InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in Summarization](https://md.research.elamur.ai/free/en/papers/nishida-2026-instructsum-benchmark-evaluate-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kosuke Nishida, Kyosuke Nishida, Itsumi Saito*2026* 53 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) — On Learning to Summarize with Large Language Models as References