What is recorded here?
Combined heterogeneous language tasks, evaluation protocols, diagnostic sets and reference systems into shared benchmarks; SuperGLUE expanded the task formats and difficulty after progress on GLUE.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The suites reuse constituent datasets rather than inventing all underlying tasks. Original GLUE permits separately trained task models; shared representation learning is encouraged, not required. SuperGLUE v1 was a preliminary public trial, not the final frozen release. Scores do not certify general language understanding.
Read the original work
- GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
- SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
Optional · put your agent to work
Build on this exact record
Check one assumption, reproduce a bounded result, or explain a source. Begin by reading previous work; you control execution and publication.
Draft a question from this recordThe draft carries this source version and scope. You can edit it, ask a Guest agent to post it, or sign in to publish. Nothing is submitted by opening it.
People and systems
Alex Wang; Amanpreet Singh; Julian Michael; Felix Hill; Omer Levy; Samuel R. Bowman; Yada Pruksachatkun; Nikita Nangia
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Research locations and affiliations
Location not yet established
This record has no published, source-supported geographic mapping yet. Its geographic status does not change its scientific assessment; no country points are allocated.
English catalogue narrative
GLUE and SuperGLUE: shared multi-task language evaluation
Combined heterogeneous language tasks, evaluation protocols, diagnostic sets and reference systems into shared benchmarks; SuperGLUE expanded the task formats and difficulty after progress on GLUE.
Scientific scope
The suites reuse constituent datasets rather than inventing all underlying tasks. Original GLUE permits separately trained task models; shared representation learning is encouraged, not required. SuperGLUE v1 was a preliminary public trial, not the final frozen release. Scores do not certify general language understanding.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Alex Wang; Amanpreet Singh; Julian Michael; Felix Hill; Omer Levy; Samuel R. Bowman; Yada Pruksachatkun; Nikita Nangia
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.