# iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration

arXiv: https://arxiv.org/abs/2109.11621 · HTML: https://mlsanity.com/paper/2109.11621/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 50 references that are in the map.
- First posted on arXiv 23 Sep 2021.

## Builds on (most cited first, 15 of 15)

- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://mlsanity.com/paper/1907.10529/) (2019)
- [CoQA: A Conversational Question Answering Challenge](https://mlsanity.com/paper/1808.07042/) (2018)
- [AllenNLP: A Deep Semantic Natural Language Processing Platform](https://mlsanity.com/paper/1803.07640/) (2018)
- [Coreference Resolution as Query-based Span Prediction](https://mlsanity.com/paper/1911.01746/) (2019)
- [Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution](https://mlsanity.com/paper/1906.01753/) (2019)
- [Query Focused Abstractive Summarization: Incorporating Query Relevance, Multi-Document Coverage, and Summary Length Constraints into seq2seq Models](https://mlsanity.com/paper/1801.07704/) (2018)
- [Cross-document Coreference Resolution over Predicted Mentions](https://mlsanity.com/paper/2106.01210/) (2021)
- [WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia](https://mlsanity.com/paper/2104.05022/) (2021)
- [Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization](https://mlsanity.com/paper/1805.10985/) (2018)
- [SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search](https://mlsanity.com/paper/2005.12668/) (2020)
- [Understanding Points of Correspondence between Sentences for Abstractive Summarization](https://mlsanity.com/paper/2006.05621/) (2020)
- [Paraphrasing vs Coreferring: Two Sides of the Same Coin](https://mlsanity.com/paper/2004.14979/) (2020)
- [Abstractive Multi-Document Summarization via Phrase Selection and Merging](https://mlsanity.com/paper/1506.01597/) (2015)
- [Virtual Location-Based Services: Merging the Physical and Virtual World](https://mlsanity.com/paper/1310.2864/) (2013)

## Built on by (most cited first, 8 of 8)

- [Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering](https://mlsanity.com/paper/2305.15387/) (2023)
- [EntSUM: A Data Set for Entity-Centric Summarization](https://mlsanity.com/paper/2204.02213/) (2022)
- [Controlled Text Reduction](https://mlsanity.com/paper/2210.13449/) (2022)
- [SEAM: A Stochastic Benchmark for Multi-Document Tasks](https://mlsanity.com/paper/2406.16086/) (2024)
- [Unbalanced Optimal Transport for Unbalanced Word Alignment](https://mlsanity.com/paper/2306.04116/) (2023)
- [PerSEval: Assessing Personalization in Text Summarizers](https://mlsanity.com/paper/2407.00453/) (2024)
- [Towards Proactive Information Retrieval in Noisy Text with Wikipedia Concepts](https://mlsanity.com/paper/2210.09877/) (2022)
- [SUMMPILOT: Bridging Efficiency and Customization for Interactive Summarization System](https://mlsanity.com/paper/2601.08475/) (2026)

## Abstract (arXiv)

We introduce iFacetSum, a web application for exploring topical document sets. iFacetSum integrates interactive summarization together with faceted search, by providing a novel faceted navigation scheme that yields abstractive summaries for the user's selections. This approach offers both a comprehensive overview as well as concise details regarding subtopics of choice. Fine-grained facets are automatically produced based on cross-document coreference pipelines, rendering generic concepts, entities and statements surfacing in the source texts. We analyze the effectiveness of our application through small-scale user studies, which suggest the usefulness of our approach.