Optimizing Denoising Trajectories in dLLMs: A Lightweight Evolutionary Heuristic Approach

arXiv:2609.26052 · cs.CL, cs.LG · Submitted 2026-07-15 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-07-15

Updated: 2026-07-15

Code: https://github.com/RS2002/Evo-Denoise

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 12× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Generalization — 7× in this paper · explained in 13 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Adaptation — 5× in this paper · explained in 1 episode
• Failure Modes — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Attention Mechanism — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• GRPO — 2× in this paper · explained in 6 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• RAG — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Block Diffusion — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Multi-hop Reasoning — 1× in this paper · explained in 3 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• GPT-4 Technical Report
• Beyond Exponential Decay: Rethinking Error Accumulation in Large Language Models
• First Token Probability Guided RAG for Telecom Question Answering
• Training Verifiers to Solve Math Word Problems
• Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models
• The CMA Evolution Strategy: A Tutorial
• MDPO: Overcoming the Training-Inference Divide of Masked Diffusion Language Models
• DeepSeek-V3 Technical Report
• When Confidence Misleads: Suffix Anchoring and Anchor-Proximity Confidence Modulation for Diffusion Language Models
• Proximal Policy Optimization Algorithms
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
• Dream 7B: Diffusion Large Language Models
• LLaDA-MoE: A Sparse MoE Diffusion Language Model

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