---
title: "Who cites Contrastive Learning with Narrative — 5 citing papers"
description: "5 papers of the Elamur Research library cite «Contrastive Learning with Narrative Twins for Modeling Story Salience», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/sterner-2026-contrastive-learning-narrative-twins-modeling/cited-by/"
---
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# Who cites «Contrastive Learning with Narrative Twins for Modeling Story Salience»

5 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 «Contrastive Learning with Narrative Twins for Modeling Story Salience»](https://md.research.elamur.ai/free/en/papers/sterner-2026-contrastive-learning-narrative-twins-modeling/)

1. **[AI-Monitors at SemEval-2026 Task 4: A Hybrid Embedding and LLM Ensemble for Narrative Similarity](https://md.research.elamur.ai/free/en/papers/tripathi-2026-ai-monitors-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Vishnu Tripathi, Prakhar Joshi, Azad Singh, et al.*2026 · 1 citation*
2. **[Spinfo Cologne at SemEval-2026 Task 4: Explainable Creation of Narrativity Embeddings](https://md.research.elamur.ai/free/en/papers/pagel-2026-spinfo-cologne-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Janis Pagel, Nils Reiter*2026 · 1 citation*
3. **[Yam at SemEval-2026 Task 4: Failure-Driven Prompt Evolution for Narrative Comparison](https://md.research.elamur.ai/free/en/papers/yam-2026-yam-semeval-2026-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Yen Yee Yam, Hong Meng Yam*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/sterner-2026-contrastive-learning-narrative-twins-modeling/) — Contrastive Learning with Narrative Twins for Modeling Story Salience