# Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections

arXiv: https://arxiv.org/abs/2302.06754 · HTML: https://mlsanity.com/paper/2302.06754/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2023.

## Built on by (most cited first, 21 of 21)

- [CiteME: Can Language Models Accurately Cite Scientific Claims?](https://mlsanity.com/paper/2407.12861/) (2024)
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- [PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers](https://mlsanity.com/paper/2403.02939/) (2024)
- [A Question Answering Framework for Decontextualizing User-facing Snippets from Scientific Documents](https://mlsanity.com/paper/2305.14772/) (2023)
- [SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers](https://mlsanity.com/paper/2411.05338/) (2024)
- [DiscipLink: Unfolding Interdisciplinary Information Seeking Process via Human-AI Co-Exploration](https://mlsanity.com/paper/2408.00447/) (2024)
- [The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces](https://mlsanity.com/paper/2303.14334/) (2023)
- [From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems](https://mlsanity.com/paper/2503.01424/) (2025)
- [AI-Enhanced Sensemaking: Exploring the Design of a Generative AI-Based Assistant to Support Genetic Professionals](https://mlsanity.com/paper/2412.15444/) (2024)
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- [Attribution Gradients: Incrementally Unfolding Citations for Critical Examination of Attributed AI Answers](https://mlsanity.com/paper/2510.00361/) (2025)
- [Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work](https://mlsanity.com/paper/2503.18471/) (2025)
- [TreeReader: A Hierarchical Academic Paper Reader Powered by Language Models](https://mlsanity.com/paper/2507.18945/) (2025)
- [LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape](https://mlsanity.com/paper/2604.02600/) (2026)
- [RealitySummary: Exploring On-Demand Mixed Reality Text Summarization and Question Answering using Large Language Models](https://mlsanity.com/paper/2405.18620/) (2024)
- [From Toil to Thought: Designing for Strategic Exploration and Responsible AI in Systematic Literature Reviews](https://mlsanity.com/paper/2603.05514/) (2026)
- [Generative Artificial Intelligence for Literature Reviews](https://mlsanity.com/paper/2605.16475/) (2026)
- [FootprintRAG: Visual Analytics for Evidence Context Refinement in RAG-based Scientific Literature Exploration](https://mlsanity.com/paper/2609.19601/) (2026)

## Abstract (arXiv)

Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly challenging. Meanwhile, authors summarize prior research in papers' related work sections, though this is scoped to support a single paper. A formative study found that while reading multiple related work paragraphs helps overview a topic, it is hard to navigate overlapping and diverging references and research foci. In this work, we design a system, Relatedly, that scaffolds exploring and reading multiple related work paragraphs on a topic, with features including dynamic re-ranking and highlighting to spotlight unexplored dissimilar information, auto-generated descriptive paragraph headings, and low-lighting of redundant information. From a within-subjects user study (n=15), we found that scholars generate more coherent, insightful, and comprehensive topic outlines using Relatedly compared to a baseline paper list.