Papers with CDCR
CDˆ2CR: Co-reference resolution across documents and domains (2021.eacl-main)
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| Challenge: | Current models for cross-document co-reference resolution assume that all documents are of the same type or fall under the same theme. |
| Approach: | They propose a task for cross-document cross-domain co-reference resolution (CD2CR) task aims to identify links between entities across heterogeneous document types. |
| Outcome: | The proposed task outperforms current state-of-the-art models on CD2CR in cross-domain, cross-document setting. |
Event Coreference Data (Almost) for Free: Mining Hyperlinks from Online News (2021.emnlp-main)
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| Challenge: | Annotating CDCR data is laborious and expensive, explaining why existing corpora are small and lack domain coverage. |
| Approach: | They use hyperlinks to extract event coreference data from online news articles . they find that models trained on small subsets of HyperCoref are highly competitive . |
| Outcome: | The proposed system frees up CDCR research from costly human-annotated training data and opens up possibilities beyond English. |
Okay, Let’s Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation (2024.naacl-long)
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| Challenge: | Recent work shows that generative large language models (LLMs) can be used to solve cross-document coreference problems. |
| Approach: | They propose rationale-oriented event clustering and knowledge distillation methods for event coreference scoring that leverage enriched information from the FTRs for improved CDCR. |
| Outcome: | The proposed model achieves SOTA B3 F1 on the ECB+ and GVC corpora without additional annotation or expensive document clustering. |
A Cross-document Coreference Dataset for Longitudinal Tracking across Radiology Reports (2022.lrec-1)
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| Challenge: | Oftentimes, these findings and devices are referred to multiple times in a single report and are also referred across different reports of a patient. |
| Approach: | They propose a new cross-document coreference resolution (CDCR) dataset for identifying co-referring radiological findings and medical devices across a patient's radiology reports. |
| Outcome: | The proposed dataset contains 5872 mentions (findings and devices) spanning 638 MIMIC-III radiology reports across 60 patients, covering multiple imaging modalities and anatomies. |
Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes (2022.lrec-1)
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| Challenge: | Existing cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. |
| Approach: | They propose to use a phrasing diversity metric to evaluate lexical diversity of CDCR datasets . they propose to combine CDCR annotation schemes with multiple properties of the coreference chains . |
| Outcome: | The proposed phrasing diversity metric evaluates the CDCR datasets with higher precision. |
Employing Discourse Coherence Enhancement to Improve Cross-Document Event and Entity Coreference Resolution (2025.acl-long)
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| Challenge: | Existing work on cross-document coreference resolution focuses on within-document events and entities, but cross-doc mentions lack such critical contexts. |
| Approach: | They propose a task to enhance the discourse coherence between two cross-document mentions by adding coherent texts to a document to form a new coherent document. |
| Outcome: | The proposed method outperforms state-of-the-art baselines on three popular datasets. |