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Diffusion LLM

5 articles · Page 1 of 1
Machine Heart
Machine Heart
Sep 10, 2026 · Artificial Intelligence

DiffuTester: Accelerating Diffusion LLM Unit Test Generation via Structural Pattern Mining

DiffuTester is a training-free framework that accelerates diffusion language model unit test generation by mining shared structural patterns across test cases via AST, enabling more tokens per denoising step and achieving 2–3× speedup while maintaining coverage across Python, C++, and Java on DiffuCoder and Dream models.

ASTCode GenerationDiffusion LLM
0 likes · 9 min read
DiffuTester: Accelerating Diffusion LLM Unit Test Generation via Structural Pattern Mining
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Mar 3, 2026 · Artificial Intelligence

Enabling Search Agents to Think While Waiting: Diffusion LLMs Deliver 15% Faster Inference Without Accuracy Loss

The paper introduces DLLM‑Searcher, which equips diffusion large language models with a two‑stage training pipeline and a P‑ReAct inference scheme, allowing the model to issue tool calls while simultaneously reasoning, yielding 14‑22% end‑to‑end speedup and matching or surpassing traditional autoregressive agents on multi‑hop QA benchmarks.

Diffusion LLMMulti-hop QAP-ReAct
0 likes · 10 min read
Enabling Search Agents to Think While Waiting: Diffusion LLMs Deliver 15% Faster Inference Without Accuracy Loss
Data Party THU
Data Party THU
Oct 10, 2025 · Artificial Intelligence

How DPad Cuts Inference Time 61× While Boosting Accuracy in Diffusion LLMs

The article analyzes a recent Duke University paper that reveals a "scratchpad" mechanism in diffusion large language models, proposes the DPad method to prune redundant suffix tokens before decoding, and demonstrates up to 61.4× faster inference with unchanged or even improved accuracy across multiple benchmarks.

DPadDiffusion LLMInference Acceleration
0 likes · 10 min read
How DPad Cuts Inference Time 61× While Boosting Accuracy in Diffusion LLMs
AI Frontier Lectures
AI Frontier Lectures
Apr 24, 2025 · Artificial Intelligence

How d1 Boosts Reasoning in Diffusion LLMs with Reinforcement Learning

Researchers from UCLA and Meta AI introduce d1, a two‑stage post‑training framework that combines supervised fine‑tuning and a novel diffu‑GRPO reinforcement‑learning algorithm to enable efficient reasoning in masked diffusion large language models, achieving state‑of‑the‑art performance on multiple math and logic benchmarks.

AIDiffusion LLMd1
0 likes · 9 min read
How d1 Boosts Reasoning in Diffusion LLMs with Reinforcement Learning