---
configs:
- config_name: add_6digit
  data_files:
  - path: add_6digit/train.parquet
    split: train
  - path: add_6digit/val.parquet
    split: validation
  - path: add_6digit/eval_stratified.parquet
    split: test
- config_name: add_sub_6digit
  data_files:
  - path: add_sub_6digit/train.parquet
    split: train
  - path: add_sub_6digit/val.parquet
    split: validation
  - path: add_sub_6digit/eval_stratified.parquet
    split: test
language:
- en
license: apache-2.0
size_categories:
- 1M<n<10M
tags:
- arithmetic
- interpretability
- sorl
- mechanistic-interpretability
- addition
- subtraction
- quirke
task_categories:
- text-generation
---

# Arithmetic SoRL Data

Training and evaluation data for the **SoRL Arithmetic Interpretability Study**.

Small transformers trained on integer addition/subtraction, with
[SoRL](https://github.com/fangyuan-ksgk/mod_gpt) to externalize carry/borrow circuits
as explicit abstraction tokens.

Reference: Quirke et al., "Understanding Addition and Subtraction in Transformers" (2024)

## Dataset Structure

| Subfolder | Operations | Train | Val | Eval (stratified) |
|---|---|---|---|---|
| `add_6digit` | addition only | 500K | 10K | ~550 (50 per S0-S6 + 200 random) |
| `add_sub_6digit` | add + sub | 500K | 10K | ~1100 (50 per S0-S6 + M0-M6 + random) |

## Columns

| Column | Type | Description |
|---|---|---|
| `tokens` | list[int] | Full sequence (21 tokens for 6-digit) |
| `labels` | list[str] | Per-answer-digit sub-task label |
| `op` | str | `"add"` or `"sub"` |
| `complexity` | str | Quirke complexity: `S0`-`S6` (add) or `M0`-`M6` (sub) |
| `cascade_depth` | int | Max carry/borrow cascade length |
| `x_digits` | list[int] | First operand (MSB first) |
| `y_digits` | list[int] | Second operand (MSB first) |
| `z_digits` | list[int] | Answer (MSB first, n_digits+1) |

The `eval_stratified` split has an additional `eval_category` column.

## Sub-task Labels (Quirke et al.)

Each answer digit requires a specific arithmetic operation:

### Addition
| Label | Name | Condition | Role |
|---|---|---|---|
| SA | Base Add | `Dn + D'n < 9`, no carry | Simplest case |
| SC | Make Carry | `Dn + D'n >= 10` | Generates carry |
| SS | Sum is 9 | `Dn + D'n == 9` | Propagates carry if one arrives |
| UC | Use Carry | carry_in=1, sum != 9 | Consumes incoming carry |
| US | Use Sum-9 | carry_in=1, sum == 9 | Cascade: hardest case |

### Subtraction (x >= y)
| Label | Name | Condition | Role |
|---|---|---|---|
| MD | Base Diff | `Dn > D'n`, no borrow | Simplest case |
| MB | Make Borrow | `Dn < D'n` | Generates borrow |
| ME | Equal digits | `Dn == D'n` | Propagates borrow if one arrives |
| UB | Use Borrow | borrow_in=1, `Dn != D'n` | Consumes incoming borrow |
| UD | Use Equal | borrow_in=1, `Dn == D'n` | Cascade: hardest case |

## Complexity Classification (Quirke Table 8)

Complexity = length of longest carry/borrow cascade chain.

Example: `555555+444448=1000003` is **S6** — the carry from D0 cascades through
5 consecutive sum-9 positions.

```
S0: no carries            ~10%
S1: isolated carries      ~50%
S2: cascade of 2          ~26%
S3: cascade of 3           ~9%
S4: cascade of 4           ~3%
S5: cascade of 5           ~1%
S6: cascade of 6          <0.5%
```

## Data Enrichment

Following Quirke: 60% of batches have 40% of digit positions forced to sum-to-9,
increasing cascade frequency so the model sees enough S4-S6 cases.

## Usage

```python
from datasets import load_dataset

ds = load_dataset("thoughtworks/arithmetic-sorl-data", data_dir="add_6digit")
print(ds["train"][0])
# {'tokens': [...], 'labels': ['SA', 'UC', 'US', ...],
#  'complexity': 'S3', 'cascade_depth': 3, ...}

# Stratified eval
eval_ds = load_dataset("thoughtworks/arithmetic-sorl-data",
                       data_dir="add_6digit", data_files="eval_stratified.parquet")
```

## Related

- Model checkpoints: [thoughtworks/arithmetic-sorl](https://huggingface.co/thoughtworks/arithmetic-sorl)
- Code: [mod_gpt/arithmetic/](https://github.com/fangyuan-ksgk/mod_gpt/tree/amir/arithmetic/arithmetic)