metadata
language:
- en
tags:
- evaluation
- reasoning
- llm
- science
- mathematics
size_categories:
- 10K<n<100K
configs:
- config_name: hle
data_files:
- split: test
path: data/hle/test-*.parquet
Lite-RSI
Lite-RSI is a multi-benchmark collection of normalized model responses and automated evaluation traces. The current release provides the hle configuration. Each row is one model response to one task. Repeated task_id values are intentional: they represent responses from different models or generation runs.
Available Configurations
| Config | Split | Description |
|---|---|---|
hle |
test |
HLE multi-model evaluation responses. |
Data Format
The dataset is published as a single standard Hugging Face Parquet shard:
data/hle/test-00000-of-00001.parquet
record_id is a unique release-level identifier. task_id identifies the underlying question. model_name identifies the normalized generating model.
| Field | Description |
|---|---|
record_id |
Unique normalized record identifier. |
task_id |
Underlying task identifier; repeats across model responses. |
model_name |
Generating model, with provider-prefix aliases normalized. |
generation_source |
Original/retry/gold/run-source label. |
prompt |
User prompt text. |
reference_answer |
Reference target from the original task. |
response |
Model completion. |
judge_label, judge_confidence, judge_answer, judge_explanation |
Existing automated-grader fields. |
subject, category, answer_type, has_image, rationale |
Original task metadata. |
sample_sha256 |
Integrity hash of the original sample. |
Loading
from datasets import load_dataset
dataset = load_dataset(
"lhpku20010120/Lite-RSI",
"hle",
split="test",
)
Data Notes
- Empty completions are retained and marked by
has_response=false. - This release does not deduplicate model outputs; comparisons across models and retries are a primary use case.
- Additional benchmarks will be published as separate dataset configurations under
data/<benchmark>/. - Before publishing, the dataset owner must confirm the licenses and redistribution rights of the original questions, answers, model outputs, and any referenced attachments.