The full conference program with a detailed schedule will be released at a later date. In the meantime, information on tutorials and other events will be published here progressively, and follow our social medias or RSS feed for updates.

Tutorial Day: Monday 30 November

ALTA 2026 will host two tutorials on the first day of the workshop. Details of the morning tutorial are below; the afternoon tutorial will be announced soon.

Morning tutorial

Title: Transfer Learning in Clinical NLP

Presenters: Distinguished Professor Karin Verspoor, Dr David Martinez Iraola, Wei Han (RMIT University)

Abstract: Machine learning models often require large, labelled datasets, making high-quality annotation costly and time-consuming. Transfer learning addresses this challenge by reusing knowledge learned from related tasks, datasets, or models to improve learning in low-resource settings. In NLP, transfer learning enables models to reuse linguistic knowledge across tasks, but differences in domains, text types, and data distributions still limit model generalisation. These challenges are particularly significant in clinical NLP, where annotation is labour-intensive and requires specialist expertise. Clinical text also varies across institutions, specialities, document types, and patient groups. Differences in terminology, abbreviations, and writing styles further reduce model generalisation. In this tutorial, we will first introduce transfer learning and its development in NLP, together with representative transfer learning methods. After that we will talk about the transfer shifts between source and target clinical settings, why transfer is important in clinical NLP, and the main challenges for its application. Hands-on exercises with accessible clinical datasets will allow participants to implement and evaluate several transfer approaches. Finally, the tutorial will discuss clinical-specific transfer learning challenges and future research directions.

Tutorial Overview:

  1. Session 1: Foundations and Methods of Clinical NLP Transfer Learning (1h)
    • Part 1: Transfer Learning in NLP — Introduces transfer learning, and explains how transfer has developed in NLP. Introduces representative methods used for transfer learning in NLP.
    • Part 2: Transfer Learning Scenarios in Clinical NLP — Explains why transfer learning is specifically valuable for clinical NLP, and gives an overview of transfer scenarios from source to target in clinical settings.
  2. Session 2: Practical Clinical Transfer Learning (1.5h)
    • Part 3: Hands-on Clinical Transfer Learning Exercise — Applies representative transfer learning methods to real-world clinical datasets and evaluates their effectiveness under realistic source-to-target shifts.
    • Part 4: Challenges and Future Directions

Pre-requisite: Basic knowledge of machine learning and NLP will help participants follow the technical content. No prior experience in clinical NLP or transfer learning is required. Some hands-on exercises will use datasets hosted on PhysioNet, which requires prior credentialed access through their website. There will also be publicly available datasets that can be accessed without credentials.

Afternoon tutorial

Details coming soon!

Main Conference: 1–2 December

The main conference program will be announced at a later date.