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Revert card to pre-cond5-edit state (moving changes to a PR)

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@@ -921,7 +921,7 @@ Prior work ([Aryabumi et al., 2024 -- "To Code or Not to Code"](https://arxiv.or
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  ## Dataset Description
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- This dataset provides filtered, quality-controlled Python source code in multiple configurations: the original English, three keyword-swapped variants (Chinese, Spanish, Urdu), a blended native+transpiled mix, strictly native Chinese code, and a model-translated set in which an LLM translates the full source (identifiers, strings, and comments, not just keywords). The source data is drawn from [bigcode/the-stack-dedup](https://huggingface.co/datasets/bigcode/the-stack-dedup) (Python subset), filtered for quality using the following criteria:
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  - AST-valid Python only (must parse without errors)
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  - Permissive licenses only (MIT, Apache-2.0, BSD, etc.)
@@ -934,7 +934,7 @@ Keyword-swapped variants are produced using [Legesher](https://github.com/legesh
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  ## Available Configs
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- Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpora, `-20k` random subsets sampled from the corresponding `-103k` config with seed 42, and `-5k` compact subsets. Phase 2 `-32k` configs are still available with the `phase-2-the-stack-v1-*` prefix. Condition 5 (`condition-5-*-c4ai-aya-expanse-32b`) is the model-translated set — currently `5k` only, and raw/pre-cleanup (see the note above).
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  | Config | Condition | Language | Description | Train | Val |
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  | ------------------------- | ----------- | -------- | ------------------------------------------------ | ------ | ------ |
@@ -952,9 +952,7 @@ Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpo
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  | `condition-2-ur-5k` | 2 | Urdu | Compact 5k subset | 4,500 | 500 |
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  | `condition-3-zh-5k` | 3 | Chinese | Blended: native Chinese code + transpiled Python | 4,500 | 500 |
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  | `condition-4-zh-5k` | 4 | Chinese | Strictly native Chinese code | 6,553 | 729 |
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- | `condition-5-ur-5k-c4ai-aya-expanse-32b` | 5 | Urdu | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,088 | 381 |
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- | `condition-5-zh-5k-c4ai-aya-expanse-32b` | 5 | Chinese | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,052 | 381 |
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- | `condition-5-es-5k-c4ai-aya-expanse-32b` | 5 | Spanish | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,032 | 329 |
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  ## Schema
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@@ -971,22 +969,6 @@ Used by: `condition-1-en-*`, `condition-2-zh-*`, `condition-2-es-*`, `condition-
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  | `license` | string | SPDX license identifier for the source file. |
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  | `token_count` | int64 | Token count computed using the CohereLabs/tiny-aya-base tokenizer. |
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- ### Condition 5
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-
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- Used by: `condition-5-ur-5k-c4ai-aya-expanse-32b`, `condition-5-zh-5k-c4ai-aya-expanse-32b`, `condition-5-es-5k-c4ai-aya-expanse-32b`
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-
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- Condition 5 uses the conditions 1--2 schema plus an `idx` column. `code` is the full LLM-translated source (identifiers, strings, comments, and keywords); `code_en` is the English original. These configs are raw model output — see the note at the top of this card.
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-
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- | Column | Type | Description |
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- | ------------- | ------ | ------------------------------------------------------------------------------------- |
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- | `code` | string | Model-translated Python source (full LLM translation via Cohere Aya). |
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- | `code_en` | string | Original English Python source code. |
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- | `language` | string | ISO 639-1 language code: `ur`, `zh`, or `es`. |
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- | `file_path` | string | Original file path in The Stack Dedup. |
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- | `license` | string | SPDX license identifier for the source file. |
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- | `idx` | int64 | Source row index into `condition-1-en-5k`. Enables row-level joins across conditions. |
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- | `token_count` | int64 | Token count computed using the CohereLabs/tiny-aya-base tokenizer. |
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-
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  ### Condition 3
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  Used by: `condition-3-zh-5k`
@@ -1033,7 +1015,6 @@ The Language Decoded experiment uses a ladder of conditions to isolate the mecha
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  | Condition 2 | Keyword-swapped code | Tests whether the _language_ of keywords matters for the reasoning benefit |
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  | Condition 3 | Mixed native sources | Tests whether diverse native-language code adds value beyond keyword swapping |
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  | Condition 4 | Strictly native code | Tests whether code authored by native speakers carries unique signal beyond transpilation |
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- | Condition 5 | Model-translated code | Tests whether full LLM translation (identifiers, strings, comments -- not just keywords) changes the reasoning benefit, relative to Condition 2's keyword-only swap |
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  ### The Experimental Ladder
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@@ -1070,11 +1051,6 @@ ds = load_dataset("legesher/language-decoded-data", "condition-3-zh-5k")
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  # Load strictly native code (condition 4)
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  ds = load_dataset("legesher/language-decoded-data", "condition-4-zh-5k")
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- # Load model-translated code (condition 5 -- raw, pre-cleanup)
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- ds = load_dataset("legesher/language-decoded-data", "condition-5-ur-5k-c4ai-aya-expanse-32b")
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- ds = load_dataset("legesher/language-decoded-data", "condition-5-zh-5k-c4ai-aya-expanse-32b")
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- ds = load_dataset("legesher/language-decoded-data", "condition-5-es-5k-c4ai-aya-expanse-32b")
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-
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  # Access splits
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  train = ds["train"]
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  val = ds["validation"]
@@ -1091,7 +1067,6 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
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  | Transpilation tool | [Legesher](https://github.com/legesher/legesher) v0.7.3 (legesher-core, legesher-i18n) |
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  | Tokenizer | CohereLabs/tiny-aya-base |
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  | Base model | [CohereLabs/tiny-aya-base](https://huggingface.co/CohereLabs/tiny-aya-base) (3.35B params) |
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- | Condition 5 translation model | Cohere `c4ai-aya-expanse-32b` (Aya Expanse 32B, via the Cohere API) |
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  | Train/validation split | 90% / 10% (seed 42) |
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  | File format | Parquet (snappy compression) |
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  | Filtering criteria | AST-valid, permissive licenses, 10--1000 lines, min 21 GitHub stars, no autogenerated files, SHA-256 deduplication |
@@ -1103,7 +1078,6 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
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  - **Token count variation**: Transpiled code may have different token counts than the English original due to multi-byte characters (especially for Chinese and Urdu), even though the code structure is identical.
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  - **Single programming language**: Currently limited to Python. Results may not generalize to other programming languages.
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  - **Condition 4 scope**: Native Chinese code is limited to publicly available sources (The Stack, Wenyan, Program-in-Chinese, Qi, Mulan) and may not represent the full spectrum of Chinese-language programming.
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- - **Condition 5 is raw model output**: The `condition-5-*` configs contain prompt-leakage contamination -- translator-model preamble text, JSON wrappers, and explanation commentary leaked into string literals and identifier names, in AST-valid and AST-invalid rows alike. Cleaned configs will be published separately. See the note at the top of this card.
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  ## Citation
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  ## Dataset Description
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+ This dataset provides filtered, quality-controlled Python source code in multiple configurations: the original English, three keyword-swapped variants (Chinese, Spanish, Urdu), a blended native+transpiled mix, and strictly native Chinese code. The source data is drawn from [bigcode/the-stack-dedup](https://huggingface.co/datasets/bigcode/the-stack-dedup) (Python subset), filtered for quality using the following criteria:
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  - AST-valid Python only (must parse without errors)
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  - Permissive licenses only (MIT, Apache-2.0, BSD, etc.)
 
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  ## Available Configs
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+ Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpora, `-20k` random subsets sampled from the corresponding `-103k` config with seed 42, and `-5k` compact subsets. Phase 2 `-32k` configs are still available with the `phase-2-the-stack-v1-*` prefix.
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  | Config | Condition | Language | Description | Train | Val |
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  | ------------------------- | ----------- | -------- | ------------------------------------------------ | ------ | ------ |
 
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  | `condition-2-ur-5k` | 2 | Urdu | Compact 5k subset | 4,500 | 500 |
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  | `condition-3-zh-5k` | 3 | Chinese | Blended: native Chinese code + transpiled Python | 4,500 | 500 |
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  | `condition-4-zh-5k` | 4 | Chinese | Strictly native Chinese code | 6,553 | 729 |
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+ | `condition-5-ur-5k-c4ai-aya-expanse-32b` | 5 | Urdu | Model-translated Urdu condition | 4,024 | 447 |
 
 
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  ## Schema
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  | `license` | string | SPDX license identifier for the source file. |
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  | `token_count` | int64 | Token count computed using the CohereLabs/tiny-aya-base tokenizer. |
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  ### Condition 3
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  Used by: `condition-3-zh-5k`
 
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  | Condition 2 | Keyword-swapped code | Tests whether the _language_ of keywords matters for the reasoning benefit |
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  | Condition 3 | Mixed native sources | Tests whether diverse native-language code adds value beyond keyword swapping |
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  | Condition 4 | Strictly native code | Tests whether code authored by native speakers carries unique signal beyond transpilation |
 
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  ### The Experimental Ladder
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  # Load strictly native code (condition 4)
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  ds = load_dataset("legesher/language-decoded-data", "condition-4-zh-5k")
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  # Access splits
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  train = ds["train"]
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  val = ds["validation"]
 
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  | Transpilation tool | [Legesher](https://github.com/legesher/legesher) v0.7.3 (legesher-core, legesher-i18n) |
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  | Tokenizer | CohereLabs/tiny-aya-base |
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  | Base model | [CohereLabs/tiny-aya-base](https://huggingface.co/CohereLabs/tiny-aya-base) (3.35B params) |
 
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  | Train/validation split | 90% / 10% (seed 42) |
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  | File format | Parquet (snappy compression) |
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  | Filtering criteria | AST-valid, permissive licenses, 10--1000 lines, min 21 GitHub stars, no autogenerated files, SHA-256 deduplication |
 
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  - **Token count variation**: Transpiled code may have different token counts than the English original due to multi-byte characters (especially for Chinese and Urdu), even though the code structure is identical.
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  - **Single programming language**: Currently limited to Python. Results may not generalize to other programming languages.
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  - **Condition 4 scope**: Native Chinese code is limited to publicly available sources (The Stack, Wenyan, Program-in-Chinese, Qi, Mulan) and may not represent the full spectrum of Chinese-language programming.
 
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  ## Citation
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