| --- |
| license: mit |
| language: |
| - en |
| task_categories: |
| - question-answering |
| pretty_name: Parametric & Arithmetic Eval |
| size_categories: |
| - n<1K |
| tags: |
| - retrieval-heads |
| - mechanistic-interpretability |
| - parametric-knowledge |
| - ablation |
| dataset_info: |
| features: |
| - name: question |
| dtype: string |
| - name: answer |
| dtype: string |
| - name: source |
| dtype: string |
| - name: index |
| dtype: int64 |
| splits: |
| - name: train |
| num_bytes: 40056 |
| num_examples: 600 |
| download_size: 16223 |
| dataset_size: 40056 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # Parametric & Arithmetic Eval |
|
|
| A 600-example control set for testing whether ablated attention heads are |
| **retrieval-specific** rather than generically important for model output. Every |
| question is answerable from the model's own parametric knowledge or by direct |
| computation — none require retrieving information from an in-context document. |
|
|
| This dataset accompanies **LOCOS** (Logit-Contribution Scoring). A retrieval-head |
| detector is only meaningful if ablating the heads it identifies degrades |
| *contextual retrieval* while leaving *non-retrieval* abilities intact. |
|
|
| ## Composition |
|
|
| 600 examples, 200 per source: |
|
|
| | `source` | Count | Task | Example question | Example answer | |
| |----------------|-------|-----------------------------|-----------------------------------------------|----------------| |
| | `city_country` | 200 | Parametric factual recall | *Which country does Tokyo belong to?* | `Japan` | |
| | `popqa` | 200 | Parametric factual recall | *Who is the father of Brandon Lee?* | `Bruce Lee` | |
| | `arithmetic` | 200 | Two-operand add/subtract | *What is (5 + 6) - 3?* | `8` | |
|
|
| ## Fields |
|
|
| | Field | Type | Description | |
| |------------|--------|-------------------------------------------------------------------| |
| | `question` | string | The prompt question. | |
| | `answer` | string | Reference answer (short form). | |
| | `source` | string | One of `city_country`, `popqa`, `arithmetic`. | |
| | `index` | int64 | Global row index (0–199 city_country, 200–399 popqa, 400–599 arithmetic). | |
| |
| ## Provenance |
| |
| - **`city_country`** — top-200 cities by population from |
| [`WorkWithData/cities`](https://huggingface.co/datasets/WorkWithData/cities), |
| reformatted as country-identification questions (country names normalised to |
| common English forms). |
| - **`popqa`** — most-popular entries from |
| [`akariasai/PopQA`](https://huggingface.co/datasets/akariasai/PopQA), ranked by |
| the geometric mean of subject/object popularity and deduplicated by |
| subject–object pair. |
| - **`arithmetic`** — random sample (seed 42) from |
| [`EleutherAI/arithmetic`](https://huggingface.co/datasets/EleutherAI/arithmetic) |
| (`arithmetic_1dc`), with the `Question:`/`Answer:` scaffolding stripped. |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("aryopg/parametric-arithmetic-eval", split="train") |
| city_country = ds.filter(lambda r: r["source"] == "city_country") |
| ``` |
|
|
| ## License |
|
|
| Released under the **MIT License**. The dataset is derived from openly available |
| sources; please also respect the licenses of the upstream datasets linked above. |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite LOCOS and PopQA: |
|
|
| ```bibtex |
| @article{gema2026locos, |
| title={Logit-Contribution Scoring Identifies Non-Literal Retrieval Heads}, |
| author={Aryo Pradipta Gema and Beatrice Alex and Pasquale Minervini}, |
| year={2026}, |
| eprint={2607.01002}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2607.01002}, |
| } |
| ``` |
|
|
| ```bibtex |
| @article{mallen2023llm_memorization, |
| title = {When Not to Trust Language Models: Investigating Effectiveness and Limitations of Parametric and Non-Parametric Memories}, |
| author = {Mallen, Alex and Asai, Akari and Zhong, Victor and Das, Rajarshi and Hajishirzi, Hannaneh and Khashabi, Daniel}, |
| journal = {arXiv preprint}, |
| year = {2022} |
| } |
| ``` |
|
|
| This dataset also benefits from: |
| - City-Country: [WorkWithData/cities](https://huggingface.co/datasets/WorkWithData/cities) |
| - Arithmetic: [EleutherAI/arithmetic](https://huggingface.co/datasets/EleutherAI/arithmetic), subset arithmetic_1dc |
| |
| > **Note:** the LOCOS citation is a placeholder pending the arXiv release. |
| |
