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20242026
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cs.CL2026

DreamReasoner-8B: Block-Size Curriculum Learning for Diffusion Reasoning Models

Zirui Wu, Lin Zheng, Jiacheng Ye +5

Block diffusion language models accelerate decoding through parallel block-wise denoising, yet whether they can be reliably scaled for long chain-of-thought (CoT) reasoning remains…

cs.CL2026

DreamOn: Diffusion Language Models For Code Infilling Beyond Fixed-size Canvas

Zirui Wu, Lin Zheng, Zhihui Xie +8

Diffusion Language Models (DLMs) present a compelling alternative to autoregressive models, offering flexible, any-order infilling without specialized prompting design. However, th…

cs.CL2025

Scaling Diffusion Language Models via Adaptation from Autoregressive Models

Shansan Gong, Shivam Agarwal, Yizhe Zhang +9

Diffusion Language Models (DLMs) have emerged as a promising new paradigm for text generative modeling, potentially addressing limitations of autoregressive (AR) models. However, c…

cs.CL2024

Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models

Jiacheng Ye, Shansan Gong, Liheng Chen +8

Recently, diffusion models have garnered significant interest in the field of text processing due to their many potential advantages compared to conventional autoregressive models.…

cs.CL2024

GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers

Qintong Li, Leyang Cui, Xueliang Zhao +2

Large language models (LLMs) have achieved impressive performance across various mathematical reasoning benchmarks. However, there are increasing debates regarding whether these mo…