| Challenge: | a privacy policy is a crucial component of any organization that allows it to legally collect, process, store, and/or distribute personal data. |
| Approach: | They propose to use a policy-document summarization dataset to enforce the summaries to include critical privacy-related entities and organization’s rationale in collecting those entities. |
| Outcome: | The proposed model improves over baselines and qualitatively evaluates the proposed model on human and qualitative data. |
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| Challenge: | Existing methods for controllable summarization fail to generate entity-centric summaries. |
| Approach: | They propose to use a human-annotated data set EntSUM to generate controllable summarization with a focus on named entities as the aspects to control. |
| Outcome: | The proposed data set shows that existing methods fail to generate entity-centric summaries. |
APPSI-139: A Parallel Corpus of English Application Privacy Policy Summarization and Interpretation (2026.acl-long)
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Pengyun Zhu, Qiheng Sun, Long Wen, Yanbo Wang, Yang Cao, Junxu Liu, Deyi Xiong, Jinfei Liu, Zhibo Wang, Kui Ren
| Challenge: | a lack of high-quality English privacy policy corpus optimized for legal clarity and readability is limiting translation of privacy policies . 139 privacy policies are often considered "incomprehensible" due to technical jargon, legal language, and convoluted grammatical structures. |
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Readability Controllable Biomedical Document Summarization (2022.findings-emnlp)
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| Challenge: | Existing controllable summarization systems for biomedical documents have little attention to readability control, leaving users with incompatible summaries . |
| Approach: | They propose a task of readability controllable summarization for biomedical documents to generate summaries that are incompatible with users' levels of expertise. |
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An Entity-Driven Framework for Abstractive Summarization (D19-1)
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| Challenge: | Popular neural summarization models produce incoherent and unfaithful summaries . however, their outputs are often incohérent and incoerent . |
| Approach: | They propose a system for ENtity-drivEn Coherent Abstractive summarization framework that leverages entity information to generate informative and coherent abstracts. |
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EntSUMv2: Dataset, Models and Evaluation for More Abstractive Entity-Centric Summarization (2023.emnlp-main)
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| Challenge: | Entity-centric summarization is a form of controllable summarizing that aims to generate a summary for a specific entity given a document. |
| Approach: | They propose to use a more abstract version of the original entity-centric ENTSUM summarization dataset to generate a shorter annotated summary for downstream users. |
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Controllable Abstractive Sentence Summarization with Guiding Entities (2020.coling-main)
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| Challenge: | Existing text summarization models lack guiding entities to ensure that entities are present in summaries. |
| Approach: | They propose a controllable abstractive sentence summarization model which generates summaries with guiding entities. |
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How Private are Language Models in Abstractive Summarization? (2025.emnlp-main)
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| Challenge: | Effective protection of private information is essential for knowledge dissemination in sensitive domains such as medical and legal. |
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Not all Hallucinations are Good to Throw Away When it Comes to Legal Abstractive Summarization (2025.naacl-long)
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| Challenge: | Existing models for summarization of legal documents rely on external knowledge to generate abstracts. |
| Approach: | They propose an entity-driven approach that learns the model to generate factual hallucinations . they evaluate legal documents in English and French to evaluate their results . |
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Enhancing Multi-Document Summarization with Cross-Document Graph-based Information Extraction (2023.eacl-main)
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| Challenge: | Information extraction (IE) and summarization (summarization) are closely related, but both aims to abstract the most salient information into a generated text summary. |
| Approach: | They propose to use structured IE graphs to enhance the abstractive summarization task by using cross-document IE output to incorporate an alignment loss between IE nodes and their text spans to reduce inconsistencies. |
| Outcome: | The proposed model can generate summaries that are more factual while not losing abstractiveness. |
Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects - A Survey (2024.findings-acl)
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| Challenge: | scholarly attention has turned to the development of text summarization methods that are more closely tailored and controlled to align with specific objectives and user needs. |
| Approach: | They formalize a controllable text summarization task and categorize controllability attributes according to their shared characteristics and objectives. |
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