AI EVALUATION, IN CONTEXT.BY EQUALITY MACHINE

Claire Radar

SciDocBench

SciDocBench evaluates scientific document understanding with 124 expert-authored questions across seven capability groups and 19 subtasks in five scientific domains. Each question is tested under four conditions (English vs Chinese and all-images-first vs interleaved), yielding 496 instances. Performance is reported on a 100-point scale. Data and pipeline are released via a public repository.

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 2026-10-14; resources and fields reflect that saved source.

Recorded attention

Observed on: 2026-10-14

GitHub stars
6
Star change · 30 days before observation
+3

internlm/scidocbench · View source snapshot

Dated attention observations, not live counts or benchmark scores.

Evaluation context and evidence

Source
Claire Radar
Publisher
Not recorded
Benchmark release
2026-09-04
Collected
2026-10-14
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.