mlsanityData to 14 Oct 2026

MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning

arXiv 2507.07419 ↗First posted 10 Jul 2025cs.CL cs.AIcited by 5

Not on the map. Why?

Abstract (arXiv)

Generative AI has demonstrated strong potential in healthcare, from clinical decision support to patient-facing chatbots that improve outcomes. A critical challenge for deployment is effective human-AI communication, where content must be both personalized and understandable. We introduce MedReadCtrl, a readability-controlled instruction tuning framework that enables LLMs to adjust output complexity without compromising meaning. Evaluations of nine datasets and three tasks across medical and general domains show that MedReadCtrl achieves significantly lower readability instruction-following errors than GPT-4 (e.g., 1.39 vs. 1.59 on ReadMe, p<0.001) and delivers substantial gains on unseen clinical tasks (e.g., +14.7 ROUGE-L, +6.18 SARI on MTSamples). Experts consistently preferred MedReadCtrl (71.7% vs. 23.3%), especially at low literacy levels. These gains reflect MedReadCtrl's ability to restructure clinical content into accessible, readability-aligned language while preserving medical intent, offering a scalable solution to support patient education and expand equitable access to AI-enabled care.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 27 of its 57 references that are in the map. First posted on arXiv 10 Jul 2025.

Builds on

27 of 57 references.

References · 27

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  4. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  5. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,682
  6. 2015A large annotated corpus for learning natural language inferencecited by 1,847
  7. 2024A Survey on LLM-as-a-Judgecited by 1,423
  8. 2023Instruction Tuning for Large Language Models: A Surveycited by 623
  9. 2019PAWS: Paraphrase Adversaries from Word Scramblingcited by 402
  10. 2018Lessons from Natural Language Inference in the Clinical Domaincited by 151
  11. 2024InFoBench: Evaluating Instruction Following Ability in Large Language Modelscited by 135
  12. 2025Preference Leakage: A Contamination Problem in LLM-as-a-judgecited by 125
15 more
  1. 2024Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Taskscited by 106
  2. 2020ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformationscited by 101
  3. 2024Controllable Text Generation for Large Language Models: A Surveycited by 57
  4. 2020Automated Lay Language Summarization of Biomedical Scientific Reviewscited by 46
  5. 2024Following Length Constraints in Instructionscited by 46
  6. 2023BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processingcited by 25
  7. 2023PaniniQA: Enhancing Patient Education Through Interactive Question Answeringcited by 21
  8. 2022MedJEx: A Medical Jargon Extraction Model with Wiki's Hyperlink Span and Contextualized Masked Language Model Scorecited by 20
  9. 2022Readability Controllable Biomedical Document Summarizationcited by 19
  10. 2023README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLPcited by 17
  11. 2025VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Recordscited by 17
  12. 2023Prompt-Based Length Controlled Generation with Reinforcement Learningcited by 14
  13. 2021Improving Formality Style Transfer with Context-Aware Rule Injectioncited by 13
  14. 2021Towards more patient friendly clinical notes through language models and ontologiescited by 4
  15. 2024Learning Personalized Prompts for Healthcare Guidancecited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Iterative Critique-Refine Framework for Enhancing LLM Personalizationcited by 1
  2. 2025MedCOD: Enhancing English-to-Spanish Medical Translation of Large Language Models Using Enriched Chain-of-Dictionary Frameworkcited by 0
  3. 2026Rethinking Patient Education as Multi-turn Multi-modal Interactioncited by 0
  4. 2026TA-RAG: Tone-Aware Retrieval-Augmented Generation for Peer-Support Health Communicationcited by 0
  5. 2026TA-RAG: Tone Awareness as a Design Imperative for Retrieval-Augmented Generationcited by 0