# VADIS -- a VAriable Detection, Interlinking and Summarization system

arXiv: https://arxiv.org/abs/2312.13423 · HTML: https://mlsanity.com/paper/2312.13423/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 12 references that are in the map.
- First posted on arXiv 20 Dec 2023.

## Builds on (most cited first, 8 of 8)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://mlsanity.com/paper/1804.05685/) (2018)
- [TLDR: Extreme Summarization of Scientific Documents](https://mlsanity.com/paper/2004.15011/) (2020)
- [A Summarization System for Scientific Documents](https://mlsanity.com/paper/1908.11152/) (2019)
- [Scientific document summarization via citation contextualization and scientific discourse](https://mlsanity.com/paper/1706.03449/) (2017)
- [X-SCITLDR: Cross-Lingual Extreme Summarization of Scholarly Documents](https://mlsanity.com/paper/2205.15051/) (2022)
- [Overview of the SV-Ident 2022 Shared Task on Survey Variable Identification in Social Science Publications](https://mlsanity.com/paper/2209.09062/) (2022)
- [Towards Automated Survey Variable Search and Summarization in Social Science Publications](https://mlsanity.com/paper/2209.06804/) (2022)

## Built on by (most cited first, 1 of 1)

- [Enriching Social Science Research via Survey Item Linking](https://mlsanity.com/paper/2412.15831/) (2024)

## Abstract (arXiv)

The VADIS system addresses the demand of providing enhanced information access in the domain of the social sciences. This is achieved by allowing users to search and use survey variables in context of their underlying research data and scholarly publications which have been interlinked with each other.