Shared Task Website: https://brandonio-c.github.io/ClinIQLink-2025/

Dear Colleague,

We are pleased to invite you to participate in ClinIQLink 2025, an evaluation 
task organized as part of the BioNLP Workshop at ACL 2025. This initiative 
focuses on assessing the ability of generative models to produce factually 
accurate medical information, particularly in the context of knowledge 
retrieval and hallucination detection.

About the Task

The ClinIQLink challenge evaluates models using a novel dataset of atomic, 
fact-based question-answer pairs aligned with the knowledge level of a General 
Practitioner (GP). Submissions will be assessed on:

  *   Knowledge Retrieval: How accurately models retrieve medical information 
about core concepts like procedures, conditions, drugs, and diagnostics.
  *   Hallucination Analysis (Post-hoc): Understanding hallucination origins in 
model responses, categorized into intrinsic (internal model issues), extrinsic 
(external information gaps), or hybrid causes.

Models will be scored based on precision, with penalties for incorrect or 
unsupported answers. Although hallucination analysis won’t affect the 
leaderboard, findings will highlight areas for improvement.

Participation Requirements

To take part in this shared task, participants must:

  *   Submit their models to CodaBench for evaluation.
  *   Provide a short paper describing the methodology, including any novel 
approaches or improvements made.

The dataset, created in collaboration with medical experts, will not be 
publicly released to ensure the evaluation's integrity.

Evaluation Details

Submissions will be evaluated using a semi-automated process with metrics for 
both closed-ended and open-ended questions:

  *   Closed-ended Questions: True/False, multiple-choice, and lists, scored 
using precision, recall, and F1 metrics.
  *   Open-ended Questions: Evaluated on exact matches or partial semantic 
similarity using semantic similarity scores (described on the shared task 
website) and, where necessary, analyzed by experts with utilizing semantic 
similarity scores, BLEU, ROUGE, METEOR, and other metrics to assist with the 
experts judgements.

Important Dates

  *   First Call for Participation: January 21, 2025
  *   Dataset and testing framework release on Codabench: February 20, 2025
  *   System submission Deadline: April 15, 2025
  *   Results Feedback: April 25, 2025
  *   Preliminary Paper Submission: May 5, 2025
  *   Final Paper Submission: May 15, 2025
  *   BioNLP Workshop at ACL 2025: July 31, 2025

For a full timeline and additional details, visit our official 
website<https://brandonio-c.github.io/ClinIQLink-2025/>.

Why Participate?

This task offers a unique opportunity to benchmark your models against 
state-of-the-art systems, advance the field of medical QA, and contribute to a 
deeper understanding of hallucination detection in generative AI.

If you have any questions, please do not hesitate to contact Brandon Colelough 
at [email protected]<mailto:[email protected]>.

We look forward to your participation in this exciting initiative.

Kind regards,

Brandon Colelough (He / Him)

[News, Events, and Updates]NIH Fellow | Fulbright Scholar | ADF Signals Officer 
| Electrical Engineer
National Institutes of Health – National Library of Medicine (LHC)
M: +61 481 269 667<tel:+61481269667> (AUS) | M: +1 (202) 
367-7230<tel:+12023677230> (US)
E: [email protected]<mailto:[email protected]> | E: 
[email protected]<mailto:[email protected]>
L: 
www.linkedin.com/in/brandon-colelough<https://gcc02.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.linkedin.com%2Fin%2Fbrandon-colelough-853296194&data=05%7C02%7Cbrandon.colelough%40nih.gov%7C72376e92177e433f45aa08dc9ac6d3b2%7C14b77578977342d58507251ca2dc2b06%7C0%7C0%7C638555425971995708%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=1I95BjjvXOCu5VFz6HyQNgbJV6RQZk9or4KY0ZjpKqw%3D&reserved=0>

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