Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents

Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Kumar Bhowmick, Aditya Vempaty, Prasenjit Dey, Ravi Kokku, Pawan Goyal, Niloy Ganguly


Abstract
Analyzing and processing vast amounts of textual data presents significant challenges in efficiently extracting key information.In this paper, we introduce '***Spotlight***’, a novel paradigm for information extraction that produces concise, engaging narratives by highlighting the most compelling aspects of a document. Unlike highlights (fragmented key points) and traditional summaries, which prioritize comprehensive coverage, spotlights selectively emphasize intriguing content to foster deeper reader engagement with the source material. We formally differentiate spotlights from related constructs and support our analysis with a detailed benchmarking study using new datasets curated for this work. To generate high-quality spotlights, we propose a two-stage approach: fine-tuning a large language model on our benchmark data, followed by alignment via Direct Preference Optimization (DPO). Our comprehensive evaluation demonstrates that the resulting model not only identifies key elements with precision but also enhances readability and boosts the engagement value of the original document. Datasets and code are available at https://github.com/ankan2/Spotlight-EMNLP2025.
Anthology ID:
2025.emnlp-main.1796
Volume:
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Christos Christodoulopoulos, Tanmoy Chakraborty, Carolyn Rose, Violet Peng
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EMNLP
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Publisher:
Association for Computational Linguistics
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Pages:
35449–35477
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https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1796/
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Cite (ACL):
Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Kumar Bhowmick, Aditya Vempaty, Prasenjit Dey, Ravi Kokku, Pawan Goyal, and Niloy Ganguly. 2025. Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 35449–35477, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents (Mullick et al., EMNLP 2025)
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