# Overview of the BioLaySumm 2024 Shared Task on the Lay Summarization of Biomedical Research Articles

arXiv: https://arxiv.org/abs/2408.08566 · HTML: https://mlsanity.com/paper/2408.08566/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 30 references that are in the map.
- First posted on arXiv 16 Aug 2024.

## Builds on (most cited first, 15 of 15)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://mlsanity.com/paper/1912.08777/) (2019)
- [BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining](https://mlsanity.com/paper/2210.10341/) (2022)
- [AlignScore: Evaluating Factual Consistency with a Unified Alignment Function](https://mlsanity.com/paper/2305.16739/) (2023)
- [BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model](https://mlsanity.com/paper/2204.03905/) (2022)
- [Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform](https://mlsanity.com/paper/2110.05802/) (2021)
- [Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature](https://mlsanity.com/paper/2210.09932/) (2022)
- [LENS: A Learnable Evaluation Metric for Text Simplification](https://mlsanity.com/paper/2212.09739/) (2022)
- [RAG-RLRC-LaySum at BioLaySumm: Integrating Retrieval-Augmented Generation and Readability Control for Layman Summarization of Biomedical Texts](https://mlsanity.com/paper/2405.13179/) (2024)
- [WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articles](https://mlsanity.com/paper/2405.11950/) (2024)

## Built on by (most cited first, 18 of 18)

- [RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Framework](https://mlsanity.com/paper/2410.19109/) (2024)
- [Evaluating the Evaluators: Are readability metrics good measures of readability?](https://mlsanity.com/paper/2508.19221/) (2025)
- [Magical: Medical Lay Language Generation via Semantic Invariance and Layperson-tailored Adaptation](https://mlsanity.com/paper/2508.08730/) (2025)
- [Confident Rankings with Fewer Items: Adaptive LLM Evaluation with Continuous Scores](https://mlsanity.com/paper/2601.13885/) (2026)
- [Compressing Language Models for Specialized Domains](https://mlsanity.com/paper/2502.18424/) (2025)
- [Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review](https://mlsanity.com/paper/2409.18170/) (2024)
- [Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasing](https://mlsanity.com/paper/2505.18867/) (2025)
- [A Critical Look at Meta-evaluating Summarisation Evaluation Metrics](https://mlsanity.com/paper/2409.19507/) (2024)
- [Are LLM-generated plain language summaries truly understandable? A large-scale crowdsourced evaluation](https://mlsanity.com/paper/2505.10409/) (2025)
- [Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents](https://mlsanity.com/paper/2509.10935/) (2025)
- [PERCS: Persona-Guided Controllable Biomedical Summarization Dataset](https://mlsanity.com/paper/2512.03340/) (2025)
- [MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Models](https://mlsanity.com/paper/2604.05738/) (2026)
- [Am I eligible? Natural Language Inference for Clinical Trial Patient Recruitment: the Patient's Point of View](https://mlsanity.com/paper/2503.15718/) (2025)
- [Making Knowledge Accessible: Divergent Readability-Accuracy Strategies of Mistral and QWen in Biomedical Text Simplification](https://mlsanity.com/paper/2511.05080/) (2025)
- [No Reader Left Behind: Multi-Agent Summaries Everyone Can Understand](https://mlsanity.com/paper/2605.28836/) (2026)
- [MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models](https://mlsanity.com/paper/2606.21194/) (2026)
- [Improving Health Literacy through Lay Summarization of Radiological Reports: An Evaluation of BioNER and Retrieval-Augmented Generation](https://mlsanity.com/paper/2609.02396/) (2026)
- [Enhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation](https://mlsanity.com/paper/2609.17398/) (2026)

## Abstract (arXiv)

This paper presents the setup and results of the second edition of the BioLaySumm shared task on the Lay Summarisation of Biomedical Research Articles, hosted at the BioNLP Workshop at ACL 2024. In this task edition, we aim to build on the first edition's success by further increasing research interest in this important task and encouraging participants to explore novel approaches that will help advance the state-of-the-art. Encouragingly, we found research interest in the task to be high, with this edition of the task attracting a total of 53 participating teams, a significant increase in engagement from the previous edition. Overall, our results show that a broad range of innovative approaches were adopted by task participants, with a predictable shift towards the use of Large Language Models (LLMs).