# Overview of BioASQ 2025: The Thirteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

arXiv: https://arxiv.org/abs/2508.20554 · HTML: https://mlsanity.com/paper/2508.20554/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 84 references that are in the map.
- First posted on arXiv 28 Aug 2025.

## Builds on (most cited first, 21 of 21)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Representation Learning with Contrastive Predictive Coding](https://mlsanity.com/paper/1807.03748/) (2018)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://mlsanity.com/paper/1901.08746/) (2019)
- [SciBERT: A Pretrained Language Model for Scientific Text](https://mlsanity.com/paper/1903.10676/) (2019)
- [Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing](https://mlsanity.com/paper/2007.15779/) (2020)
- [Language-agnostic BERT Sentence Embedding](https://mlsanity.com/paper/2007.01852/) (2020)
- [Self-Alignment Pretraining for Biomedical Entity Representations](https://mlsanity.com/paper/2010.11784/) (2020)
- [LinkBERT: Pretraining Language Models with Document Links](https://mlsanity.com/paper/2203.15827/) (2022)
- [Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling](https://mlsanity.com/paper/2010.11304/) (2020)
- [GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer](https://mlsanity.com/paper/2311.08526/) (2023)
- [Biomedical Entity Representations with Synonym Marginalization](https://mlsanity.com/paper/2005.00239/) (2020)
- [NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data](https://mlsanity.com/paper/2402.15343/) (2024)
- [Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking](https://mlsanity.com/paper/2105.14398/) (2021)
- [Overview of BioASQ 2021: The ninth BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answering](https://mlsanity.com/paper/2106.14885/) (2021)
- [Overview of BioASQ 2023: The eleventh BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answering](https://mlsanity.com/paper/2307.05131/) (2023)
- [NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities](https://mlsanity.com/paper/2210.11913/) (2022)
- [Overview of BioASQ 2022: The tenth BioASQ challenge on Large-Scale Biomedical Semantic Indexing and Question Answering](https://mlsanity.com/paper/2210.06852/) (2022)
- [Beyond Retrieval: Ensembling Cross-Encoders and GPT Rerankers with LLMs for Biomedical QA](https://mlsanity.com/paper/2507.05577/) (2025)
- [Can Language Models Critique Themselves? Investigating Self-Feedback for Retrieval Augmented Generation at BioASQ 2025](https://mlsanity.com/paper/2508.05366/) (2025)
- [Harnessing Collective Intelligence of LLMs for Robust Biomedical QA: A Multi-Model Approach](https://mlsanity.com/paper/2508.01480/) (2025)

## Built on by (most cited first, 11 of 11)

- [MaLei at MultiClinSUM: Summarisation of Clinical Documents using Perspective-Aware Iterative Self-Prompting with LLMs](https://mlsanity.com/paper/2509.07622/) (2025)
- [A Domain-Specific Curated Benchmark for Entity and Document-Level Relation Extraction](https://mlsanity.com/paper/2602.04320/) (2026)
- [Reason2Decide: Rationale-Driven Multi-Task Learning](https://mlsanity.com/paper/2512.20074/) (2025)
- [Efficient and Reliable Estimation of Named Entity Linking Quality: A Case Study on GutBrainIE](https://mlsanity.com/paper/2601.06624/) (2026)
- [BIBERT-Pipe on Biomedical Nested Named Entity Linking at BioASQ 2025](https://mlsanity.com/paper/2509.09725/) (2025)
- [Are Smaller Open-Weight LLMs Closing the Gap to Proprietary Models for Biomedical Question Answering?](https://mlsanity.com/paper/2509.18843/) (2025)
- [Enhancing Biomedical Named Entity Recognition using GLiNER-BioMed with Targeted Dictionary-Based Post-processing for BioASQ 2025 task 6](https://mlsanity.com/paper/2510.08588/) (2025)
- [Investigating LLM Capabilities on Long Context Comprehension for Medical Question Answering](https://mlsanity.com/paper/2510.18691/) (2025)
- [Beyond Correctness: Validity-Oriented Evaluation of Biomedical LLM Judges](https://mlsanity.com/paper/2608.29127/) (2026)
- [BELXTR: Biomedical Entity Linking via Contextualized Token Retrieval](https://mlsanity.com/paper/2609.25859/) (2026)
- [Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering](https://mlsanity.com/paper/2609.39975/) (2026)

## Abstract (arXiv)

This is an overview of the thirteenth edition of the BioASQ challenge in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2025. BioASQ is a series of international challenges promoting advances in large-scale biomedical semantic indexing and question answering. This year, BioASQ consisted of new editions of the two established tasks, b and Synergy, and four new tasks: a) Task MultiClinSum on multilingual clinical summarization. b) Task BioNNE-L on nested named entity linking in Russian and English. c) Task ELCardioCC on clinical coding in cardiology. d) Task GutBrainIE on gut-brain interplay information extraction. In this edition of BioASQ, 83 competing teams participated with more than 1000 distinct submissions in total for the six different shared tasks of the challenge. Similar to previous editions, several participating systems achieved competitive performance, indicating the continuous advancement of the state-of-the-art in the field.