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Update dataset card with Quirke complexity labels

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  1. README.md +67 -51
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@@ -11,6 +11,7 @@ tags:
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  - mechanistic-interpretability
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  - addition
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  - subtraction
 
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  size_categories:
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  - 1M<n<10M
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  ---
@@ -19,65 +20,77 @@ size_categories:
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  Training and evaluation data for the **SoRL Arithmetic Interpretability Study**.
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- We train small transformers on integer addition and subtraction, then use
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- [Self-Organizing Reinforcement Learning (SoRL)](https://github.com/fangyuan-ksgk/mod_gpt)
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- to externalize the model's carry/borrow circuits as explicit abstraction tokens.
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  Reference: Quirke et al., "Understanding Addition and Subtraction in Transformers" (2024)
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  ## Dataset Structure
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- Each subfolder contains `train.parquet`, `val.parquet`, and `config.json`.
 
 
 
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- | Subfolder | Digits | Operations | Train | Val | Sequence Length |
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- |---|---|---|---|---|---|
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- | `add_6digit` | 6 | addition | 500K | 10K | 21 tokens |
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- | `add_sub_6digit` | 6 | add + sub | 500K | 10K | 21 tokens |
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- | `add_4digit` | 4 | addition | 500K | 10K | 15 tokens |
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- | `add_sub_4digit` | 4 | add + sub | 500K | 10K | 15 tokens |
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- ## Format
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-
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- Each row has:
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- - **tokens**: list of ints — the full input sequence (operands + operator + answer)
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- - **labels**: list of str — per-answer-digit sub-task label
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- - **op**: `"add"` or `"sub"`
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- - **x_digits**, **y_digits**, **z_digits**: the raw digit lists (MSB first)
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-
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- ### Token format
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-
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- Addition: `XXXXXX+YYYYYY=ZZZZZZZ` (n_digits + operator + n_digits + equals + n_digits+1)
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-
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- Subtraction: `XXXXXX-YYYYYY=ZZZZZZZ` (x >= y guaranteed, answer zero-padded)
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-
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- Token IDs: 0-9 = digits, 10 = `+`, 11 = `=`, 12 = `-`
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-
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- ### Sub-task labels
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-
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- Each answer digit is labeled with the arithmetic sub-task it requires:
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-
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- **Addition:**
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- | Label | Name | Description |
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- |---|---|---|
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- | BA | Base Add | Simple addition, no carry |
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- | MC1 | Make Carry | digit_sum >= 10, generates carry |
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- | MS9 | Make Sum 9 | digit_sum == 9, propagates carry if present |
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- | UC1 | Use Carry | carry_in=1, digit_sum != 9 |
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- | US9 | Use Sum 9 | carry_in=1, digit_sum == 9 (cascade, hardest) |
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-
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- **Subtraction:**
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- | Label | Name | Description |
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  |---|---|---|
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- | BS | Base Sub | Simple subtraction, no borrow |
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- | MB1 | Make Borrow | x_i < y_i, needs borrow |
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- | MD9 | Make Diff 9 | x_i == y_i, propagates borrow if present |
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- | UB1 | Use Borrow | borrow_in=1, x_i != y_i |
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- | UD9 | Use Diff 9 | borrow_in=1, x_i == y_i (cascade, hardest) |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Data Enrichment
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- Following Quirke et al.: 60% of batches have 40% of digit positions forced to sum-to-9,
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- increasing the frequency of US9 (carry cascade) examples from ~6% to ~8%.
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  ## Usage
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@@ -86,12 +99,15 @@ from datasets import load_dataset
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  ds = load_dataset("thoughtworks/arithmetic-sorl-data", data_dir="add_6digit")
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  print(ds["train"][0])
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- # {'tokens': [1, 2, 3, 4, 5, 6, 10, 6, 5, 4, 3, 2, 1, 11, 0, 7, 7, 7, 7, 7, 7],
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- # 'labels': ['BA', 'UC1', 'MS9', ...], 'op': 'add', ...}
 
 
 
 
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  ```
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  ## Related
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  - Model checkpoints: [thoughtworks/arithmetic-sorl](https://huggingface.co/thoughtworks/arithmetic-sorl)
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  - Code: [mod_gpt/arithmetic/](https://github.com/fangyuan-ksgk/mod_gpt/tree/amir/arithmetic/arithmetic)
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- - SoRL paper: Yu & Abdullah, "Intention-Level Alignment with Weak Supervision" (2025)
 
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  - mechanistic-interpretability
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  - addition
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  - subtraction
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+ - quirke
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  size_categories:
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  - 1M<n<10M
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  ---
 
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  Training and evaluation data for the **SoRL Arithmetic Interpretability Study**.
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+ Small transformers trained on integer addition/subtraction, with
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+ [SoRL](https://github.com/fangyuan-ksgk/mod_gpt) to externalize carry/borrow circuits
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+ as explicit abstraction tokens.
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  Reference: Quirke et al., "Understanding Addition and Subtraction in Transformers" (2024)
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  ## Dataset Structure
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+ | Subfolder | Operations | Train | Val | Eval (stratified) |
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+ |---|---|---|---|---|
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+ | `add_6digit` | addition only | 500K | 10K | ~550 (50 per S0-S6 + 200 random) |
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+ | `add_sub_6digit` | add + sub | 500K | 10K | ~1100 (50 per S0-S6 + M0-M6 + random) |
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+ ## Columns
 
 
 
 
 
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+ | Column | Type | Description |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  |---|---|---|
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+ | `tokens` | list[int] | Full sequence (21 tokens for 6-digit) |
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+ | `labels` | list[str] | Per-answer-digit sub-task label |
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+ | `op` | str | `"add"` or `"sub"` |
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+ | `complexity` | str | Quirke complexity: `S0`-`S6` (add) or `M0`-`M6` (sub) |
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+ | `cascade_depth` | int | Max carry/borrow cascade length |
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+ | `x_digits` | list[int] | First operand (MSB first) |
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+ | `y_digits` | list[int] | Second operand (MSB first) |
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+ | `z_digits` | list[int] | Answer (MSB first, n_digits+1) |
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+
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+ The `eval_stratified` split has an additional `eval_category` column.
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+
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+ ## Sub-task Labels (Quirke et al.)
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+
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+ Each answer digit requires a specific arithmetic operation:
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+
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+ ### Addition
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+ | Label | Name | Condition | Role |
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+ |---|---|---|---|
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+ | SA | Base Add | `Dn + D'n < 9`, no carry | Simplest case |
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+ | SC | Make Carry | `Dn + D'n >= 10` | Generates carry |
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+ | SS | Sum is 9 | `Dn + D'n == 9` | Propagates carry if one arrives |
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+ | UC | Use Carry | carry_in=1, sum != 9 | Consumes incoming carry |
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+ | US | Use Sum-9 | carry_in=1, sum == 9 | Cascade: hardest case |
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+
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+ ### Subtraction (x >= y)
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+ | Label | Name | Condition | Role |
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+ |---|---|---|---|
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+ | MD | Base Diff | `Dn > D'n`, no borrow | Simplest case |
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+ | MB | Make Borrow | `Dn < D'n` | Generates borrow |
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+ | ME | Equal digits | `Dn == D'n` | Propagates borrow if one arrives |
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+ | UB | Use Borrow | borrow_in=1, `Dn != D'n` | Consumes incoming borrow |
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+ | UD | Use Equal | borrow_in=1, `Dn == D'n` | Cascade: hardest case |
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+
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+ ## Complexity Classification (Quirke Table 8)
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+
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+ Complexity = length of longest carry/borrow cascade chain.
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+
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+ Example: `555555+444448=1000003` is **S6** — the carry from D0 cascades through
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+ 5 consecutive sum-9 positions.
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+
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+ ```
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+ S0: no carries ~10%
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+ S1: isolated carries ~50%
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+ S2: cascade of 2 ~26%
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+ S3: cascade of 3 ~9%
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+ S4: cascade of 4 ~3%
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+ S5: cascade of 5 ~1%
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+ S6: cascade of 6 <0.5%
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+ ```
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  ## Data Enrichment
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+ Following Quirke: 60% of batches have 40% of digit positions forced to sum-to-9,
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+ increasing cascade frequency so the model sees enough S4-S6 cases.
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  ## Usage
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  ds = load_dataset("thoughtworks/arithmetic-sorl-data", data_dir="add_6digit")
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  print(ds["train"][0])
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+ # {'tokens': [...], 'labels': ['SA', 'UC', 'US', ...],
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+ # 'complexity': 'S3', 'cascade_depth': 3, ...}
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+
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+ # Stratified eval
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+ eval_ds = load_dataset("thoughtworks/arithmetic-sorl-data",
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+ data_dir="add_6digit", data_files="eval_stratified.parquet")
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  ```
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  ## Related
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  - Model checkpoints: [thoughtworks/arithmetic-sorl](https://huggingface.co/thoughtworks/arithmetic-sorl)
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  - Code: [mod_gpt/arithmetic/](https://github.com/fangyuan-ksgk/mod_gpt/tree/amir/arithmetic/arithmetic)