docs: fix condition-4-zh-5k glob pattern to use train-* (files renamed) (#9)

- docs: fix condition-4-zh-5k glob pattern to use train-* (files renamed) (09081e23a1b0b5a18656d1e6817cba9213a10e54)

README.md

@@ -1,255 +1,324 @@
 ---
 language:
-- en
-- zh
-- es
-- ur
+  - en
+  - zh
+  - es
+  - ur
 license: apache-2.0
 task_categories:
-- text-generation
+  - text-generation
 tags:
-- code
-- multilingual
-- legesher
-- transpilation
-- tiny-aya-expedition
-- language-decoded
+  - code
+  - multilingual
+  - legesher
+  - transpilation
+  - tiny-aya-expedition
+  - language-decoded
 pretty_name: Language Decoded Data
 size_categories:
-- 10K<n<100K
+  - 100K<n<1M
 configs:
-- config_name: condition-1-en
-  data_files:
-  - split: train
-    path: data/condition-1-en/train-*
-  - split: validation
-    path: data/condition-1-en/validation-*
-- config_name: condition-1-en-5k
-  data_files:
-  - split: train
-    path: data/condition-1-en-5k/train-*
-  - split: validation
-    path: data/condition-1-en-5k/validation-*
-- config_name: condition-2-es
-  data_files:
-  - split: train
-    path: data/condition-2-es/train-*.parquet
-  - split: validation
-    path: data/condition-2-es/validation-*.parquet
-- config_name: condition-2-es-5k
-  data_files:
-  - split: train
-    path: data/condition-2-es-5k/train-*
-  - split: validation
-    path: data/condition-2-es-5k/validation-*
-- config_name: condition-2-ur
-  data_files:
-  - split: train
-    path: data/condition-2-ur/train-*.parquet
-  - split: validation
-    path: data/condition-2-ur/validation-*.parquet
-- config_name: condition-2-ur-5k
-  data_files:
-  - split: train
-    path: data/condition-2-ur-5k/train-*
-  - split: validation
-    path: data/condition-2-ur-5k/validation-*
-- config_name: condition-2-zh
-  data_files:
-  - split: train
-    path: data/condition-2-zh/train-*
-  - split: validation
-    path: data/condition-2-zh/validation-*
-- config_name: condition-2-zh-5k
-  data_files:
-  - split: train
-    path: data/condition-2-zh-5k/train-*
-  - split: validation
-    path: data/condition-2-zh-5k/validation-*
-- config_name: condition-3-zh-5k
-  data_files:
-  - split: train
-    path: data/condition-3-zh-5k/train-*
-  - split: validation
-    path: data/condition-3-zh-5k/validation-*
+  - config_name: condition-1-en-32k
+    data_files:
+      - split: train
+        path: data/condition-1-en-32k/train-*
+      - split: validation
+        path: data/condition-1-en-32k/validation-*
+  - config_name: condition-1-en-5k
+    data_files:
+      - split: train
+        path: data/condition-1-en-5k/train-*
+      - split: validation
+        path: data/condition-1-en-5k/validation-*
+  - config_name: condition-2-es-32k
+    data_files:
+      - split: train
+        path: data/condition-2-es-32k/train-*
+      - split: validation
+        path: data/condition-2-es-32k/validation-*
+  - config_name: condition-2-es-5k
+    data_files:
+      - split: train
+        path: data/condition-2-es-5k/train-*
+      - split: validation
+        path: data/condition-2-es-5k/validation-*
+  - config_name: condition-2-ur-32k
+    data_files:
+      - split: train
+        path: data/condition-2-ur-32k/train-*
+      - split: validation
+        path: data/condition-2-ur-32k/validation-*
+  - config_name: condition-2-ur-5k
+    data_files:
+      - split: train
+        path: data/condition-2-ur-5k/train-*
+      - split: validation
+        path: data/condition-2-ur-5k/validation-*
+  - config_name: condition-2-zh-32k
+    data_files:
+      - split: train
+        path: data/condition-2-zh-32k/train-*
+      - split: validation
+        path: data/condition-2-zh-32k/validation-*
+  - config_name: condition-2-zh-5k
+    data_files:
+      - split: train
+        path: data/condition-2-zh-5k/train-*
+      - split: validation
+        path: data/condition-2-zh-5k/validation-*
+  - config_name: condition-3-zh-5k
+    data_files:
+      - split: train
+        path: data/condition-3-zh-5k/train-*
+      - split: validation
+        path: data/condition-3-zh-5k/validation-*
+  - config_name: condition-4-zh-5k
+    data_files:
+      - split: train
+        path: data/condition-4-zh-5k/train-*
+      - split: validation
+        path: data/condition-4-zh-5k/validation-*
 dataset_info:
-- config_name: condition-1-en
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 403718262
-    num_examples: 31818
-  - name: validation
-    num_bytes: 42626910
-    num_examples: 3536
-  download_size: 164619518
-  dataset_size: 446345172
-- config_name: condition-1-en-5k
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 55261555
-    num_examples: 4500
-  - name: validation
-    num_bytes: 6365959
-    num_examples: 500
-  download_size: 22897728
-  dataset_size: 61627514
-- config_name: condition-2-es-5k
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 55864731
-    num_examples: 4500
-  - name: validation
-    num_bytes: 6432095
-    num_examples: 500
-  download_size: 23031674
-  dataset_size: 62296826
-- config_name: condition-2-ur-5k
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 56906247
-    num_examples: 4500
-  - name: validation
-    num_bytes: 6545730
-    num_examples: 500
-  download_size: 23158039
-  dataset_size: 63451977
-- config_name: condition-2-zh
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 405515831
-    num_examples: 31818
-  - name: validation
-    num_bytes: 45065811
-    num_examples: 3536
-  download_size: 165387142
-  dataset_size: 450581642
-- config_name: condition-2-zh-5k
-  features:
-  - name: file_path
-    dtype: string
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 55793642
-    num_examples: 4500
-  - name: validation
-    num_bytes: 6422792
-    num_examples: 500
-  download_size: 22978834
-  dataset_size: 62216434
-- config_name: condition-3-zh-5k
-  features:
-  - name: file_path
-    dtype: large_string
-  - name: code
-    dtype: large_string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: large_string
-  - name: license
-    dtype: large_string
-  - name: token_count
-    dtype: int64
-  - name: source_type
-    dtype: large_string
-  splits:
-  - name: train
-    num_bytes: 40782466
-    num_examples: 4500
-  - name: validation
-    num_bytes: 4531385
-    num_examples: 500
-  download_size: 17299185
-  dataset_size: 45313851
-- config_name: default
-  features:
-  - name: code
-    dtype: string
-  - name: code_en
-    dtype: string
-  - name: language
-    dtype: string
-  - name: file_path
-    dtype: string
-  - name: license
-    dtype: string
-  - name: token_count
-    dtype: int64
+  - config_name: condition-1-en-32k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 403718262
+        num_examples: 31818
+      - name: validation
+        num_bytes: 42626910
+        num_examples: 3536
+    download_size: 164619518
+    dataset_size: 446345172
+  - config_name: condition-1-en-5k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 55261555
+        num_examples: 4500
+      - name: validation
+        num_bytes: 6365959
+        num_examples: 500
+    download_size: 22897728
+    dataset_size: 61627514
+  - config_name: condition-2-es-32k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 408041994
+        num_examples: 31818
+      - name: validation
+        num_bytes: 43090956
+        num_examples: 3536
+    download_size: 166000000
+    dataset_size: 451132950
+  - config_name: condition-2-es-5k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 55864731
+        num_examples: 4500
+      - name: validation
+        num_bytes: 6432095
+        num_examples: 500
+    download_size: 23031674
+    dataset_size: 62296826
+  - config_name: condition-2-ur-32k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 415552907
+        num_examples: 31818
+      - name: validation
+        num_bytes: 43879443
+        num_examples: 3536
+    download_size: 166000000
+    dataset_size: 459432350
+  - config_name: condition-2-ur-5k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 56906247
+        num_examples: 4500
+      - name: validation
+        num_bytes: 6545730
+        num_examples: 500
+    download_size: 23158039
+    dataset_size: 63451977
+  - config_name: condition-2-zh-32k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 405515831
+        num_examples: 31818
+      - name: validation
+        num_bytes: 45065811
+        num_examples: 3536
+    download_size: 165387142
+    dataset_size: 450581642
+  - config_name: condition-2-zh-5k
+    features:
+      - name: file_path
+        dtype: string
+      - name: code
+        dtype: string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: string
+      - name: license
+        dtype: string
+      - name: token_count
+        dtype: int32
+    splits:
+      - name: train
+        num_bytes: 55793642
+        num_examples: 4500
+      - name: validation
+        num_bytes: 6422792
+        num_examples: 500
+    download_size: 22978834
+    dataset_size: 62216434
+  - config_name: condition-3-zh-5k
+    features:
+      - name: file_path
+        dtype: large_string
+      - name: code
+        dtype: large_string
+      - name: code_en
+        dtype: string
+      - name: language
+        dtype: large_string
+      - name: license
+        dtype: large_string
+      - name: token_count
+        dtype: int64
+      - name: source_type
+        dtype: large_string
+    splits:
+      - name: train
+        num_bytes: 40782466
+        num_examples: 4500
+      - name: validation
+        num_bytes: 4531385
+        num_examples: 500
+    download_size: 17299185
+    dataset_size: 45313851
+  - config_name: condition-4-zh-5k
+    features:
+      - name: filename
+        dtype: string
+      - name: content
+        dtype: string
+      - name: extension
+        dtype: string
+      - name: source
+        dtype: string
+      - name: quality_tier
+        dtype: string
+      - name: sha256
+        dtype: string
+      - name: byte_size
+        dtype: int64
+      - name: total_lines
+        dtype: int64
+      - name: cjk_ratio
+        dtype: float64
+      - name: has_cjk
+        dtype: bool
+    splits:
+      - name: train
+        num_bytes: 44246508
+        num_examples: 6553
+      - name: validation
+        num_bytes: 7522476
+        num_examples: 729
+    download_size: 18300000
+    dataset_size: 51768984
 ---
 
 # Language Decoded | Multilingual Code Dataset
@@ -264,7 +333,7 @@ Prior work ([Aryabumi et al., 2024 -- "To Code or Not to Code"](https://arxiv.or
 
 ## Dataset Description
 
-This dataset provides filtered, quality-controlled Python source code in four configurations: the original English and three keyword-swapped variants (Chinese, Spanish, Urdu). 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:
+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:
 
 - AST-valid Python only (must parse without errors)
 - Permissive licenses only (MIT, Apache-2.0, BSD, etc.)
@@ -277,18 +346,27 @@ Keyword-swapped variants are produced using [Legesher](https://github.com/legesh
 
 ## Available Configs
 
-| Config                | Condition             | Language | Description                                                                                      |
-| --------------------- | --------------------- | -------- | ------------------------------------------------------------------------------------------------ |
-| `condition-1-en`      | Condition 1 (control) | English  | Unmodified filtered Python from The Stack Dedup                                                  |
-| `condition-2-ur`      | Condition 2           | Urdu     | Keyword-swapped Python -- 37 keywords, 72 builtins, 66 exceptions translated via Legesher v0.7.3 |
-| `condition-2-zh`      | Condition 2           | Chinese  | Keyword-swapped Python -- same transpilation method                                              |
-| `condition-2-es`      | Condition 2           | Spanish  | Keyword-swapped Python -- same transpilation method                                              |
-| `condition-3-zh-5k`   | Condition 3           | Chinese  | Blended: 3,486 native Chinese code + 1,514 transpiled Python (see Condition 3 section below)     |
+Each condition is available in two sizes: `-32k` (full filtered corpus, ~31.8k train + ~3.5k validation) and `-5k` (stratified subset, 4.5k train + 500 validation). The `-5k` subsets are used for QLoRA fine-tuning on consumer GPUs.
+
+| Config               | Condition   | Language | Description                                                  | Train  | Val   |
+| -------------------- | ----------- | -------- | ------------------------------------------------------------ | ------ | ----- |
+| `condition-1-en-32k` | 1 (control) | English  | Unmodified filtered Python from The Stack Dedup              | 31,818 | 3,536 |
+| `condition-1-en-5k`  | 1 (control) | English  | Stratified 5k subset of condition-1                          | 4,500  | 500   |
+| `condition-2-zh-32k` | 2           | Chinese  | Keyword-swapped Python via Legesher v0.7.3                   | 31,818 | 3,536 |
+| `condition-2-zh-5k`  | 2           | Chinese  | Stratified 5k subset of condition-2-zh                       | 4,500  | 500   |
+| `condition-2-es-32k` | 2           | Spanish  | Keyword-swapped Python via Legesher v0.7.3                   | 31,818 | 3,536 |
+| `condition-2-es-5k`  | 2           | Spanish  | Stratified 5k subset of condition-2-es                       | 4,500  | 500   |
+| `condition-2-ur-32k` | 2           | Urdu     | Keyword-swapped Python via Legesher v0.7.3                   | 31,818 | 3,536 |
+| `condition-2-ur-5k`  | 2           | Urdu     | Stratified 5k subset of condition-2-ur                       | 4,500  | 500   |
+| `condition-3-zh-5k`  | 3           | Chinese  | Blended: 3,486 native Chinese code + 1,514 transpiled Python | 4,500  | 500   |
+| `condition-4-zh-5k`  | 4           | Chinese  | Strictly native Chinese code (no transpiled code)            | 6,553  | 729   |
 
 ## Schema
 
 ### Conditions 1--2
 
+Used by: `condition-1-en-*`, `condition-2-zh-*`, `condition-2-es-*`, `condition-2-ur-*`
+
 | Column        | Type   | Description                                                                                                                                          |
 | ------------- | ------ | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `code`        | string | Python source code. For condition-2 configs, this is the transpiled (keyword-swapped) version. For condition-1, this is the original English source. |
@@ -300,6 +378,8 @@ Keyword-swapped variants are produced using [Legesher](https://github.com/legesh
 
 ### Condition 3
 
+Used by: `condition-3-zh-5k`
+
 Condition 3 blends native Chinese code with transpiled code and adds a `source_type` column to distinguish them. `code_en` is populated for transpiled rows (keeping them in sync with conditions 1--2) but null for native code rows, which have no English equivalent.
 
 | Column        | Type        | Description                                                                        |
@@ -312,34 +392,66 @@ Condition 3 blends native Chinese code with transpiled code and adds a `source_t
 | `token_count` | int64       | Token count computed using the CohereLabs/tiny-aya-base tokenizer                  |
 | `source_type` | string      | `"native"` (natively Chinese-authored) or `"transpiled"` (keyword-swapped English) |
 
+### Condition 4
+
+Used by: `condition-4-zh-5k`
+
+Condition 4 contains strictly native Chinese code -- code written by developers who think and code in Chinese. This uses the same schema as the [language-decoded-community](https://huggingface.co/datasets/legesher/language-decoded-community) dataset rather than the transpilation schema, since there is no English original to reference.
+
+| Column         | Type    | Description                                                    |
+| -------------- | ------- | -------------------------------------------------------------- |
+| `filename`     | string  | Original filename                                              |
+| `content`      | string  | The code content                                               |
+| `extension`    | string  | File extension (e.g., `.py`, `.c`, `.wenyan`)                  |
+| `source`       | string  | Data source (e.g., `thestack`, `wenyan`, `program_in_chinese`) |
+| `quality_tier` | string  | Quality rating: `A` (highest) through `D` (lowest)             |
+| `sha256`       | string  | SHA-256 hash for deduplication                                 |
+| `byte_size`    | int64   | File size in bytes                                             |
+| `total_lines`  | int64   | Total line count                                               |
+| `cjk_ratio`    | float64 | Ratio of CJK characters in the file                            |
+| `has_cjk`      | bool    | Whether the file contains CJK characters                       |
+
 ## Experimental Conditions
 
-The Language Decoded experiment uses a ladder of six conditions to isolate the mechanism behind code's reasoning benefit. This dataset currently provides data for conditions 1 and 2:
+The Language Decoded experiment uses a ladder of conditions to isolate the mechanism behind code's reasoning benefit:
 
-| Condition       | Name                 | Purpose                                                                                   |
-| --------------- | -------------------- | ----------------------------------------------------------------------------------------- |
-| Baseline        | No fine-tuning       | Establishes the performance floor                                                         |
-| Condition 1     | English code         | Tests whether code fine-tuning helps at all (replicates Aryabumi et al.)                  |
-| Condition 2     | Keyword-swapped code | Tests whether the _language_ of keywords matters for the reasoning benefit                |
-| Condition 3     | Mixed native sources | Tests whether diverse native-language code adds value beyond keyword swapping              |
-| Conditions 4--6 | (planned)            | Additional controls not yet included in this dataset                                      |
+| Condition   | Name                 | Purpose                                                                                   |
+| ----------- | -------------------- | ----------------------------------------------------------------------------------------- |
+| Baseline    | No fine-tuning       | Establishes the performance floor                                                         |
+| Condition 1 | English code         | Tests whether code fine-tuning helps at all (replicates Aryabumi et al.)                  |
+| Condition 2 | Keyword-swapped code | Tests whether the _language_ of keywords matters for the reasoning benefit                |
+| Condition 3 | Mixed native sources | Tests whether diverse native-language code adds value beyond keyword swapping             |
+| Condition 4 | Strictly native code | Tests whether code authored by native speakers carries unique signal beyond transpilation |
+
+### The Experimental Ladder
+
+- **Baseline --> 1**: Does code help at all?
+- **1 --> 2**: Does the language of keywords matter?
+- **2 --> 3**: Does diversity of native-language sources add value beyond keyword swap?
+- **3 --> 4**: Does code written in the cultural context of a language carry something that transpiled+mixed can't?
 
 ## Usage
 
 ```python
 from datasets import load_dataset
 
-# Load English code (control)
-ds = load_dataset("legesher/language-decoded-data", "condition-1-en")
+# Load full-size English code (control)
+ds = load_dataset("legesher/language-decoded-data", "condition-1-en-32k")
+
+# Load 5k subset (for QLoRA fine-tuning)
+ds = load_dataset("legesher/language-decoded-data", "condition-1-en-5k")
 
-# Load a keyword-swapped variant
-ds = load_dataset("legesher/language-decoded-data", "condition-2-ur")
-ds = load_dataset("legesher/language-decoded-data", "condition-2-zh")
-ds = load_dataset("legesher/language-decoded-data", "condition-2-es")
+# Load keyword-swapped variants
+ds = load_dataset("legesher/language-decoded-data", "condition-2-zh-5k")
+ds = load_dataset("legesher/language-decoded-data", "condition-2-es-5k")
+ds = load_dataset("legesher/language-decoded-data", "condition-2-ur-5k")
 
 # Load blended native + transpiled (condition 3)
 ds = load_dataset("legesher/language-decoded-data", "condition-3-zh-5k")
 
+# Load strictly native code (condition 4)
+ds = load_dataset("legesher/language-decoded-data", "condition-4-zh-5k")
+
 # Access splits
 train = ds["train"]
 val = ds["validation"]
@@ -360,12 +472,20 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
 | File format            | Parquet (snappy compression)                                                                                       |
 | Filtering criteria     | AST-valid, permissive licenses, 10--1000 lines, min 21 GitHub stars, no autogenerated files, SHA-256 deduplication |
 
+## Limitations
+
+- **Source bias**: The Stack Dedup skews toward popular, well-starred GitHub repositories, which may not represent the full diversity of Python code in the wild.
+- **Keyword-only transpilation**: Legesher translates Python reserved words (keywords, builtins, exceptions) but leaves comments, docstrings, string literals, and variable/function names in their original language (typically English). This means condition-2 code is a hybrid of translated keywords and English identifiers.
+- **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.
+- **Single programming language**: Currently limited to Python. Results may not generalize to other programming languages.
+- **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.
+
 ## Citation
 
 ```bibtex
 @misc{language-decoded-2026,
   title={Language Decoded: Investigating Language-Dependent vs. Structure-Dependent Reasoning Benefits of Code},
-  author={Madison Edgar and Saad Bazaz and Rafay Mustafa and Sarah Jawaid and Rashik Shahjahan and Khojasteh Mirza and Sohaib Bazaz},
+  author={Madison Edgar and Saad Ahmed Bazaz and Tom Sherborne and Rashik Shahjahan and Khojasteh Mirza and Sarah Jawaid and Rafay Mustafa and Sohaib Ahmed Bazaz},
   year={2026},
   publisher={Hugging Face},
   url={https://huggingface.co/datasets/legesher/language-decoded-data}
@@ -377,6 +497,9 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
 - [Legesher on GitHub](https://github.com/legesher/legesher)
 - [Tiny Aya Expedition](https://aya.for.ai)
 - [bigcode/the-stack-dedup](https://huggingface.co/datasets/bigcode/the-stack-dedup)
+- [Language Decoded Community (native code)](https://huggingface.co/datasets/legesher/language-decoded-community)
+- [Language Decoded Experiments (tracking)](https://huggingface.co/datasets/legesher/language-decoded-experiments)
+- [Language Decoded LoRA (model hub)](https://huggingface.co/legesher/language-decoded-lora)
 
 ## License