Data to 14 Oct 2026

Dream-Coder 7B: An Open Diffusion Language Model for Code

arXiv 2509.01142 ↗First posted 1 Sep 2025cs.CLcited by 81

On the map: Diffusion models → Discrete and text diffusion

Abstract (arXiv)

We present Dream-Coder 7B, an open-source discrete diffusion language model for code generation that exhibits emergent any-order generation capabilities. Unlike traditional autoregressive (AR) models that decode strictly left-to-right, Dream-Coder 7B adaptively determines its decoding strategy based on the coding task: sketch-first generation for complex algorithms, left-to-right generation for straightforward completions, and interleaved reasoning generation for code understanding tasks. We adapt a pretrained AR checkpoint to a discrete diffusion frameworks with a continuous-time weighted cross-entropy objective. Our post-training recipe comprises (i) supervised fine-tuning, where we mitigate padding pathologies via random truncation and a padding penalty to improve sample efficiency and stabilize generation; and (ii) reinforcement learning with verifiable rewards over a curated high-quality prompt set drawn from open-source datasets, using a tailored reinforcement learning recipe for diffusion language models. The resulting Dream-Coder 7B Instruct attains 21.4% pass@1 on LiveCodeBench (2410--2505) and demonstrates competitive performance on HumanEval, MBPP, BigCodeBench, and CRUXEval. We release Dream-Coder-7B and Dream-Coder-7B-Instruct checkpoints, training recipes, preprocessing pipelines, and inference code to facilitate reproducibility and further research.

Key facts. Cited by 81 papers in the map (data through 14 Oct 2026). Placed in Discrete and text diffusion, one of 14 directions in Diffusion models. Builds on 52 of its 60 references that are in the map. First posted on arXiv 1 Sep 2025.

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52 of 60 references.

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Other references · 40

2021Training Verifiers to Solve Math Word Problemscited by 10,109
2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
2021Evaluating Large Language Models Trained on Codecited by 8,320
2020Measuring Massive Multitask Language Understandingcited by 7,963
2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
2019HellaSwag: Can a Machine Really Finish Your Sentence?cited by 4,100
2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
2021Program Synthesis with Large Language Modelscited by 3,637
2019PIQA: Reasoning about Physical Commonsense in Natural Languagecited by 2,883
2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,879
2025DAPO: An Open-Source LLM Reinforcement Learning System at Scalecited by 2,810
2023Code Llama: Open Foundation Models for Codecited by 2,139

28 more

2024LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Codecited by 2,004
2024Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameterscited by 1,986
2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,719
2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,391
2024Qwen2.5-Coder Technical Reportcited by 1,203
2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,181
2024The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scalecited by 1,160
2021Variational Diffusion Modelscited by 1,153
2022Diffusion-LM Improves Controllable Text Generationcited by 1,027
2017RACE: Large-scale ReAding Comprehension Dataset From Examinationscited by 861
2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 574
2024BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructionscited by 546
2022A Continuous Time Framework for Discrete Denoising Modelscited by 451
2025Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decodingcited by 420
2024DataComp-LM: In search of the next generation of training sets for language modelscited by 398
2024CRUXEval: A Benchmark for Code Reasoning, Understanding and Executioncited by 300
2025SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolutioncited by 263
2025Mercury: Ultra-Fast Language Models Based on Diffusioncited by 235
2025dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Cachingcited by 169
2024The pitfalls of next-token predictioncited by 160
2024LLM Critics Help Catch LLM Bugscited by 147
2025Competitive Programming with Large Reasoning Modelscited by 119
2025KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Codingcited by 119
2025Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspectivecited by 76
2024FullStack Bench: Evaluating LLMs as Full Stack Coderscited by 58
2025CodeI/O: Condensing Reasoning Patterns via Code Input-Output Predictioncited by 55
2025Teaching Language Models to Critique via Reinforcement Learningcited by 42
2025Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLMcited by 13

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 21; 2026: 60.

81 papers.

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2025A Survey of Reinforcement Learning for Large Reasoning Modelscited by 180
2025LLaDA2.0: Scaling Up Diffusion Language Models to 100Bcited by 166
2025dParallel: Learnable Parallel Decoding for dLLMscited by 65
2025Diffusion Language Models are Super Data Learnerscited by 48
2025WeDLM: Reconciling Diffusion Language Models with Standard Causal Attention for Fast Inferencecited by 41
2026d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillationcited by 37
2025Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speedcited by 33
2025Training Optimal Large Diffusion Language Modelscited by 25
2026Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decodingcited by 24
2025Diffusion LLM with Native Variable Generation Lengths: Let [EOS] Lead the Waycited by 22
2025Structuring The Future: Diffusion LLM Speculative Decoding via Calibrated Draft Graphscited by 21
2026DreamOn: Diffusion Language Models For Code Infilling Beyond Fixed-size Canvascited by 19

38 more

2025Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbonecited by 18
2026The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Modelscited by 18
2026DMax: Aggressive Parallel Decoding for dLLMscited by 18
2025d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Modelscited by 17
2025Ultra-Fast Language Generation via Discrete Diffusion Divergence Instructcited by 16
2025Soft-Masked Diffusion Language Modelscited by 16
2025From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligencecited by 15
2025Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Modelcited by 13
2026Stable-DiffCoder: Pushing the Frontier of Code Diffusion Large Language Modelcited by 13
2025AutoCode: LLMs as Problem Setters for Competitive Programmingcited by 11
2025Rainbow Padding: Mitigating Early Termination in Instruction-Tuned Diffusion LLMscited by 10
2026Stop Training for the Worst: Progressive Unmasking Accelerates Masked Diffusion Trainingcited by 10
2025Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection to Diffusion Language Modelscited by 7
2026Lookahead-then-Verify: Reliable Constrained Decoding for Diffusion LLMs under Context-Free Grammarscited by 7
2026LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learningcited by 7
2025Decoding Large Language Diffusion Models with Foreseeing Movementcited by 6
2025Diffusion Language Models are Provably Optimal Parallel Samplerscited by 6
2026Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decodingcited by 6
2026Don't Retrain, Align: Adapting Autoregressive LMs to Diffusion LMs via Representation Alignmentcited by 6
2026DreamReasoner-8B: Block-Size Curriculum Learning for Diffusion Reasoning Modelscited by 5
2025WavefrontDiffusion: Dynamic Decoding Schedule for Improved Reasoningcited by 4
2026Improving Variable-Length Generation in Diffusion Language Models via Length Regularizationcited by 4
2026NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMscited by 4
2026Latent Reasoning with Normalizing Flowscited by 4
2026Entropy Aware Reward Guidance for Diffusion Language Model Alignmentcited by 3
2026DICE: Diffusion Large Language Models Excel at Generating CUDA Kernelscited by 3
2026dTRPO: Trajectory Reduction in Policy Optimization of Diffusion Large Language Modelscited by 3
2026Locally Coherent Parallel Decoding in Diffusion Language Modelscited by 3
2026TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decodingcited by 3
2026Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Modelscited by 3
2026Mosaic: Unlocking Long-Context Inference for Diffusion LLMs via Global Memory Planning and Dynamic Peak Tamingcited by 2
2026Diffusion LMs Can Approximate Optimal Infilling Lengths Implicitlycited by 2
2026UnMaskFork: Test-Time Scaling for Masked Diffusion via Deterministic Action Branchingcited by 2
2026Discrete Tilt Matchingcited by 2
2026TrustLDM: Benchmarking Trustworthiness in Language Diffusion Modelscited by 2
2026SimSD: Simple Speculative Decoding in Diffusion Language Modelscited by 2
2026Sangam: Efficiently Serving Diffusion LLMs with the AR Stackcited by 2
2026Distilled Continuous Diffusion Language Models Can Write Code in Few Steps---or Onecited by 2

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