PanCanBench is a benchmark of 282 de-identified authentic pancreatic cancer patient questions paired with 3,130expert-designed rubrics for evaluating large language models(LLM).
PanCanBench is distributed as a structured JSON dataset. Each entry corresponds to a single real-world patient or caregiver question and contains a detailed, multi-item scoring rubric.
Each question includes:
question_number (int) β Unique identifier for the questionquestion_text (string) β De-identified authentic patient or caregiver questionrubric_items (list) β A list of structured grading criteriaEach rubric item includes:
item_number (int) β Unique identifier within the questiondescription (string) β Detailed scoring criterionmin_points (int) β Minimum possible scoremax_points (int) β Maximum possible scoreEach rubric item is scored within a range of β10 to +10 points.
{
"question_number": 13,
"question_text": "My loved one has been on chemotherapy for 6 months and the CA 19-9 levels are not going down. Does this mean the treatment isnβt working?",
"rubric_items": [
{
"item_number": 1,
"description": "The response should state that doctors use imaging results to determine response to therapy.",
"min_points": 0,
"max_points": 10
},
{
"item_number": 2,
"description": "The response should state that CA 19-9 is one part of what determines response to therapy.",
"min_points": 0,
"max_points": 10
},
{
"item_number": 3,
"description": "The response should state that CA 19-9 levels are not always correlated with tumor size or disease status, and note that some patients do not secrete CA 19-9 at all.",
"min_points": 0,
"max_points": 10
}
]
}
3 commits
PanCanBench is a benchmark of 282 de-identified authentic pancreatic cancer patient questions paired with 3,130expert-designed rubrics for evaluating large language models(LLM).
PanCanBench is distributed as a structured JSON dataset. Each entry corresponds to a single real-world patient or caregiver question and contains a detailed, multi-item scoring rubric.
Each question includes:
question_number (int) β Unique identifier for the questionquestion_text (string) β De-identified authentic patient or caregiver questionrubric_items (list) β A list of structured grading criteriaEach rubric item includes:
item_number (int) β Unique identifier within the questiondescription (string) β Detailed scoring criterionmin_points (int) β Minimum possible scoremax_points (int) β Maximum possible scoreEach rubric item is scored within a range of β10 to +10 points.
{
"question_number": 13,
"question_text": "My loved one has been on chemotherapy for 6 months and the CA 19-9 levels are not going down. Does this mean the treatment isnβt working?",
"rubric_items": [
{
"item_number": 1,
"description": "The response should state that doctors use imaging results to determine response to therapy.",
"min_points": 0,
"max_points": 10
},
{
"item_number": 2,
"description": "The response should state that CA 19-9 is one part of what determines response to therapy.",
"min_points": 0,
"max_points": 10
},
{
"item_number": 3,
"description": "The response should state that CA 19-9 levels are not always correlated with tumor size or disease status, and note that some patients do not secrete CA 19-9 at all.",
"min_points": 0,
"max_points": 10
}
]
}
3 commits