Showing all evaluation blueprints that have been tagged with...
Showing all evaluation blueprints that have been tagged with "format-sensitivity".
Combined blueprint covering multiple data formats. Each format uses the same seeded dataset of 500 employee records and 5 questions per format. We measure exact-match numeric retrieval per prompt.
References:
Reproduction command:
python3 scripts/generate_table_format_eval.py --combined --formats json,csv,xml,yaml,html,markdown_table,markdown_kv,ini,pipe_delimited,jsonl,natural_language --num-records 500 --per-format-questions 5 --temperatures 0.0, 0.1 --systems null --out-dir blueprints/table-format-sensitivity --models CORE,FRONTIER
Avg. Hybrid Score
Latest:
Unique Versions: 1
Combined blueprint covering multiple data formats. Each format uses the same seeded dataset of 30 employee records and 5 questions per format. We measure exact-match numeric retrieval per prompt.
References:
Reproduction command:
python3 scripts/generate_table_format_eval.py --combined --formats json,csv,xml,yaml,html,markdown_table,markdown_kv,ini,pipe_delimited,jsonl,natural_language --num-records 30 --per-format-questions 5 --temperatures 0.0, 0.1, 0.2 --systems both --out-dir blueprints/table-format-sensitivity --models CORE,FRONTIER
Avg. Hybrid Score
Latest:
Unique Versions: 1
Combined blueprint covering multiple data formats. Each format uses the same seeded dataset of 30 employee records and 5 questions per format. We measure exact-match numeric retrieval per prompt.
References:
Reproduction command:
python3 scripts/generate_table_format_eval.py --combined --formats json,csv,xml,yaml,html,markdown_table,markdown_kv,ini,pipe_delimited,jsonl,natural_language --num-records 30 --per-format-questions 5 --temperatures 0.0, 0.1, 0.2 --systems both --out-dir blueprints/table-format-sensitivity --models CORE,FRONTIER
Avg. Hybrid Score
Latest:
Unique Versions: 1