ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks

arXiv:2609.29102 · cs.CL, cs.LG · Submitted 2026-09-24 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-24

Updated: 2026-10-08

Code: https://github.com/pengzhangzhi/Open-dLLM

Terminology

• Accuracy — 31× in this paper · explained in 1 episode
• Alignment — 31× in this paper · explained in 1 episode
• Decode — 30× in this paper · explained in 2 episodes
• Benchmark — 25× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Diffusion Model — 8× in this paper · explained in 8 episodes
• Embeddings — 8× in this paper · explained in 2 episodes
• Distillation — 7× in this paper · explained in 2 episodes
• Entanglement — 7× in this paper · explained in 3 episodes
• Flow Matching — 6× in this paper · explained in 8 episodes
• Diffusion Models — 5× in this paper · explained in 6 episodes
• Wasserstein Distance — 5× in this paper · explained in 4 episodes
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Embedded Language Flows — 3× in this paper
• Self-Distillation — 3× in this paper · explained in 7 episodes
• Thinking mode — 3× in this paper · explained in 2 episodes
• 2-Wasserstein Distance — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Block Diffusion — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Latent Reasoning — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Perplexity — 1× in this paper · explained in 3 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs
• SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
• Program Synthesis with Large Language Models
• Flow map matching with stochastic interpolants: A mathematical framework for consistency models
• How to build a consistency model: Learning flow maps via self-distillation
• Large Language Models to Diffusion Finetuning
• LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling
• Language Modeling with Hyperspherical Flows
• Continuous diffusion for categorical data
• Continuous Language Diffusion as a Decoder-Interface Problem
• Discrete Flow Matching
• Likelihood-Based Diffusion Language Models
• Edit Flows: Flow Matching with Edit Operations
• Measuring Massive Multitask Language Understanding
• Measuring Mathematical Problem Solving With the MATH Dataset
• ELF: Embedded Language Flows
• No Other Representation Component Is Needed: Diffusion Transformers Can Provide Representation Guidance by Themselves
• TextLDM: Language Modeling with Continuous Latent Diffusion
• LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
• Just on Time: Token-Level Early Stopping for Diffusion Language Models

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