Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation
arXiv 2609.02942v1•9958291cc7ea6bb25e2e993f5beca57ef725e2adf3a23f029b45463d430366a9
Paper metadata
- arXiv ID
- 2609.02942
- Version
- v1
- Category
- cs.AI, cs.CL
- Authors
- Anshul Bagaria, Sowmya S Sundaram, Gokul S Krishnan, Balaraman Ravindran
- Publication date
- 2026-09-04T04:00:00Z
- Source identifier
- 2609.02942v1
- Public record ID
- record:sha256:9958291cc7ea6bb25e2e993f5beca57ef725e2adf3a23f029b45463d430366a9
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Evidence and limitations
- Source ID
- arxiv_research
- Record identifier
- 9958291cc7ea6bb25e2e993f5beca57ef725e2adf3a23f029b45463d430366a9
- Record type
- Source metadata
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