AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

OpenCompass Hub

MedHallTune

Whether medical vision-language models give grounded answers rather than plausible hallucinations.

Cited research guide; original source measurements remain independent.

Task and evidence

Medical images are paired with instructions and ground-truth annotations. Both hallucination and non-hallucination samples matter.

MedHallTune — original paper

Read the metrics separately

The paper evaluates clinical accuracy, relevance, detail and risk. A single average can hide different failure patterns across positive and hallucination samples.

MedHallTune — original paper

Inspect the evaluation workflow

The authors provide image data, validation annotations and a JSONL prediction workflow. Inspect the evaluator and split before comparing runs.

MedHallTune — authors’ project

What this record establishes

This guide explains the linked research. The catalog has not collected a structured score table for this record; absence here does not mean the paper reports no experiments.

MedHallTune — original paper

Evidence available for this benchmark

Numeric results have not been collected for this source record. Use the paper, code or dataset below to check the task and experiments; this does not imply that the original work contains no results.

Start with these resources

Cited documents and dates (1)

Catalog collected on 2026-08-18; resources and fields reflect that saved source.

Evaluation context and evidence

Source
OpenCompass Hub
Publisher
The Chinese University of Hong Kong
Benchmark release
2025-02-28
Collected
2026-08-18
Modality
Not recorded

These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.

Reported results 0

This source record has no numeric results in our collection. That does not mean a score of zero or that no public results exist. Consult the original resources above.