SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
Paper
• 2510.09541 • Published
• 17
puzzle string | solution string |
|---|---|
0321003004002100 | 4321123434122143 |
1400000032104020 | 1432234132144123 |
0010000402400421 | 4312213412433421 |
0300210000011043 | 4312213434211243 |
0102203040001020 | 3142243142131324 |
0132030100001020 | 4132234132141423 |
1400020000434020 | 1432321421434321 |
0000430204300104 | 1243431224313124 |
1200340101400000 | 1234342121434312 |
2000030204001203 | 2134431234211243 |
0020320143020000 | 1423324143122134 |
4002010000043420 | 4312214312343421 |
2430104000130000 | 2431134242133124 |
0100200143100040 | 3124243143121243 |
1400200402400020 | 1432231432414123 |
0402103020030020 | 3412123421434321 |
1003020001304002 | 1423324121344312 |
0310100000202043 | 4312123434212143 |
0204402003000031 | 3214412313422431 |
0014002040002041 | 3214142341322341 |
3120020300000041 | 3124421314322341 |
0030000203010123 | 1234341223414123 |
4003010203002001 | 4213314213242431 |
0000004234200130 | 4213134234212134 |
0200400203040013 | 3241413213242413 |
2030102400000042 | 2431132442133142 |
0000120400434001 | 3412123421434321 |
0000010202401403 | 2314413232411423 |
0014010004010042 | 3214412324311342 |
2031034000003020 | 2431134242133124 |
0230400030122000 | 1234432134122143 |
4301010300300004 | 4321214314323214 |
4003002000302041 | 4213312414322341 |
0010200002300321 | 3412214312344321 |
2000013200041020 | 2341413232141423 |
0010040043202040 | 3214143243212143 |
0001200304020210 | 4321214314323214 |
2100300012300002 | 2143342112344312 |
3004000214030300 | 3214413214232341 |
0000210403100240 | 3421213443121243 |
0200300241002040 | 1234341241232341 |
0400230432000020 | 1432231432414123 |
0040000210200314 | 3241413214232314 |
0213002004020300 | 4213312414322341 |
0203300000410402 | 4213312423411432 |
0243430000120000 | 1243432134122134 |
0004030014230001 | 2134431214233241 |
0320003120003010 | 1324423121433412 |
0300024320300002 | 4321124321343412 |
0003401004001230 | 2143431234211234 |
0012204003001200 | 3412214343211234 |
0143002000303200 | 2143432114323214 |
3410000020304300 | 3412124321344321 |
0040300201340020 | 1243341221344321 |
2003030201040030 | 2413134231244231 |
2041103030200000 | 2341143231244213 |
0210010423000030 | 4213312423411432 |
2003302040310000 | 2413312442311342 |
0342000100004013 | 1342243131244213 |
1003024003004030 | 1423324123144132 |
0040400102101030 | 2143432132141432 |
2401000410000210 | 2431312413424213 |
0203300041002004 | 1243342141322314 |
2000314210000010 | 2431314213244213 |
2130000030211000 | 2134431234211243 |
0031012010024000 | 2431312413424213 |
1024000342000002 | 1324241342313142 |
2010400000410023 | 2314413232411423 |
4020030000323001 | 4123231414323241 |
0430021020004100 | 1432321423414123 |
0040030202340001 | 2143431212343421 |
0000003101433010 | 1324423121433412 |
0200401200033020 | 1234431221433421 |
3200010200411000 | 3214413223411423 |
0001004002031304 | 2431314242131324 |
0043002140002100 | 1243342143122134 |
3401000301004002 | 3421124321344312 |
0300213000200041 | 4312213414233241 |
2004040001233000 | 2314143241233241 |
2000402000023041 | 2314412314323241 |
0304403021000002 | 1324423121433412 |
1002000321000021 | 1342421321343421 |
0020420014300001 | 3124421314322341 |
1400300000030341 | 1432321441232341 |
0200004024300104 | 4213134224313124 |
4013030000003140 | 4213132424313142 |
0100403020030042 | 3124423124131342 |
0310200034001040 | 4312213434211243 |
0210400000411003 | 3214413223411423 |
0020230110043000 | 4123234112343412 |
4023031000400002 | 4123231432411432 |
0200403000101403 | 3241413223141423 |
0400210000200231 | 3412214313244231 |
0034000120400410 | 1234432121433412 |
0430000403012100 | 1432321443212143 |
1030300000120043 | 1234342143122143 |
0241000320041000 | 3241412323141432 |
3410000000202140 | 3412123443212143 |
1320201000000140 | 1324241342313142 |
0230001240002300 | 1234341241232341 |
Standard benchmark dataset for evaluating reasoning capabilities of diffusion language models (dLLMs). This is the dataset used in the following papers:
4x4 Sudoku puzzles represented as 16-character strings, where 0 denotes an empty cell and digits 1-4 denote filled cells.
| Split | Examples |
|---|---|
| Train | 1,000,000 |
| Test | 500 |
Each example contains two fields:
puzzle: 16-character string representing the puzzle (0 = empty cell)solution: 16-character string representing the completed gridpuzzle: 0010000402400421
solution: 4312213412433421
Every 4 characters form one row of the 4x4 grid:
Puzzle: Solution:
0 0 | 1 0 4 3 | 1 2
0 0 | 0 4 2 1 | 3 4
----+---- ----+----
0 2 | 4 0 1 2 | 4 3
0 4 | 2 1 3 4 | 2 1
The standard setup used in d1/d2/SPG:
<reasoning>...</reasoning><answer>...</answer>)The following is the actual prompt format used in d1/d2/SPG for training and evaluation:
[System]
Please solve the following 4x4 Sudoku puzzle. The puzzle is provided as a 16-character
string reading left-to-right, top-to-bottom, where '0' represents empty cells.
Rules:
- Fill empty cells with digits 1-4
- Each row must contain digits 1-4 exactly once
- Each column must contain digits 1-4 exactly once
- Each 2x2 box must contain digits 1-4 exactly once
Important: Your solution must be a COMPLETE 16-character string with only the digits 1-4,
representing your final solved grid.
Respond in this exact format:
<reasoning>
Your step-by-step solving process
</reasoning>
<answer>
[16-character solution string with no spaces or separators]
</answer>
[User]
Solve the following Sudoku puzzle: 0321003004002100
Expected model output (example - actual CoT content varies by model):
<reasoning>
The puzzle grid is:
0 3 | 2 1
0 0 | 3 0
----+----
0 4 | 0 0
2 1 | 0 0
Row 1: has 3,2,1 → missing 4 → position 0 = 4
Row 2: has 3 → need 1,2,4
Col 0: has 2 → need 1 or 4; Box0: has 3 → R1C0=4, so need 1 → position 4 = 1
Col 1: has 3,4,1 → need 2 → position 5 = 2
Col 3: has 1 → need 2,3,4; Row2 needs 4 → position 7 = 4
Row 3: has 4 → need 1,2,3
Col 2: has 2,3 → need 1 or 4; Row3 needs 1,2,3 → position 10 = 1
Col 3: has 1,4 → need 2 or 3; Box3: has 1 → position 11 = 2
Row 4: has 2,1 → need 3,4
Col 2: has 2,3,1 → need 4 → position 14 = 4
Col 3: has 1,4,2 → need 3 → position 15 = 3
</reasoning>
<answer>
4321123434122143
</answer>
@article{zhao2025d1,
title={d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning},
author={Zhao, Yanchen and Diao, Shitian and Bao, Hanze and Nie, Shuai and Wang, Juntao and Zhang, Min},
journal={arXiv preprint arXiv:2504.12216},
year={2025}
}
@article{wang2026d2,
title={d2: Improved Techniques for Training Reasoning Diffusion Language Models},
author={Wang, Guanghan and Turok, Gilad and Schiff, Yair and Arriola, Marianne and Kuleshov, Volodymyr},
journal={arXiv preprint arXiv:2509.21474},
year={2026}
}
@article{spg2025,
title={SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models},
author={Facebook Research},
journal={arXiv preprint arXiv:2510.09541},
year={2025}
}