mlsanityData to 7 Oct 2026

Design Challenges for a Multi-Perspective Search Engine

arXiv 2112.08357 ↗First posted 15 Dec 2021cs.CL cs.IRcited by 7

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Abstract (arXiv)

Many users turn to document retrieval systems (e.g. search engines) to seek answers to controversial questions. Answering such user queries usually require identifying responses within web documents, and aggregating the responses based on their different perspectives. Classical document retrieval systems fall short at delivering a set of direct and diverse responses to the users. Naturally, identifying such responses within a document is a natural language understanding task. In this paper, we examine the challenges of synthesizing such language understanding objectives with document retrieval, and study a new perspective-oriented document retrieval paradigm. We discuss and assess the inherent natural language understanding challenges in order to achieve the goal. Following the design challenges and principles, we demonstrate and evaluate a practical prototype pipeline system. We use the prototype system to conduct a user survey in order to assess the utility of our paradigm, as well as understanding the user information needs for controversial queries.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 17 of its 44 references that are in the map. First posted on arXiv 15 Dec 2021.

Builds on

17 of 44 references.

References · 17

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  12. 2020From Arguments to Key Points: Towards Automatic Argument Summarizationcited by 60
5 more
  1. 2020QED: A Framework and Dataset for Explanations in Question Answeringcited by 55
  2. 2019Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answeringcited by 48
  3. 2019Corpus Wide Argument Mining -- a Working Solutioncited by 36
  4. 2021MultiOpEd: A Corpus of Multi-Perspective News Editorialscited by 13
  5. 2019PerspectroScope: A Window to the World of Diverse Perspectivescited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 3; 2026: 1.

7 papers.