@inproceedings{cachola-etal-2026-fine,
title = "Fine-grained Readability Controlled Summarization of Scientific Documents via Control Vectors",
author = "Cachola, Isabel and
Sasse, Kuleen and
Dredze, Mark",
editor = "Mysore, Sheshera and
Kumar, Sachin and
Balachandran, Vidhisha and
Hayati, Shirley Anugrah and
Brahman, Faeze and
Moussa, Hanane Nour and
Salemi, Alireza",
booktitle = "Proceedings of the Second Workshop on Customizable {NLP}: Progress and Challenges in Customizing {NLP} for a Domain, Application, Group, or Individual ({C}ustom{NLP}4{U})",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.customnlp4u-1.10/",
pages = "97--116",
ISBN = "979-8-89176-396-8",
abstract = "Plain Language Summarization (PLS) generates summaries of technical documents accessible to non-expert audiences. Readability {--} commonly used to evaluate PLS {--} has often been treated coarsely (expert vs. lay) although it exists on a spectrum with different levels for different readers. We propose a light weight control vector method for fine-grained readability control in scientific summarization along with a requirements-based framework for data selection. Our framework enforces: (1) readability levels differ substantially, and (2) paired examples share comparable content. Under this, control vectors enable more precise readability control than other popular methods."
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%0 Conference Proceedings
%T Fine-grained Readability Controlled Summarization of Scientific Documents via Control Vectors
%A Cachola, Isabel
%A Sasse, Kuleen
%A Dredze, Mark
%Y Mysore, Sheshera
%Y Kumar, Sachin
%Y Balachandran, Vidhisha
%Y Hayati, Shirley Anugrah
%Y Brahman, Faeze
%Y Moussa, Hanane Nour
%Y Salemi, Alireza
%S Proceedings of the Second Workshop on Customizable NLP: Progress and Challenges in Customizing NLP for a Domain, Application, Group, or Individual (CustomNLP4U)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-396-8
%F cachola-etal-2026-fine
%X Plain Language Summarization (PLS) generates summaries of technical documents accessible to non-expert audiences. Readability – commonly used to evaluate PLS – has often been treated coarsely (expert vs. lay) although it exists on a spectrum with different levels for different readers. We propose a light weight control vector method for fine-grained readability control in scientific summarization along with a requirements-based framework for data selection. Our framework enforces: (1) readability levels differ substantially, and (2) paired examples share comparable content. Under this, control vectors enable more precise readability control than other popular methods.
%U https://aclanthology.org/2026.customnlp4u-1.10/
%P 97-116
Markdown (Informal)
[Fine-grained Readability Controlled Summarization of Scientific Documents via Control Vectors](https://aclanthology.org/2026.customnlp4u-1.10/) (Cachola et al., CustomNLP4U 2026)
ACL