Plan-and-Patch: Diffusion Language Models for Agentic Planning
cs.AI, cs.CL, cs.LG
Submitted: 2026-10-07
Updated: 2026-10-07
Code: https://github.com/inclusionAI/LLaDA2.X
Terminology
Sources
- From Output to Evaluation: Does Raw Instruction-Tuned Code LLMs Output Suffice for Fill-in-the-Middle Code Generation?
- Is Conditional Generative Modeling all you need for Decision-Making?
- Structured Denoising Diffusion Models in Discrete State-Spaces
- Efficient Training of Language Models to Fill in the Middle
- Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
- Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
- Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
- InCoder: A Generative Model for Code Infilling and Synthesis
- DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
- ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents
- Mercury: Ultra-Fast Language Models Based on Diffusion
- Planning with Diffusion for Flexible Behavior Synthesis
- Beyond Next-Token Prediction: A Performance Characterization of Diffusion versus Autoregressive Language Models
- Localizing and Correcting Errors for LLM-based Planners
- Code as Policies: Language Model Programs for Embodied Control
- REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction
- Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
- The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check
- Repair or Resample? Rethinking Failure Debugging in LLM Multi-Agent Systems
- Diffusion In Diffusion: Reclaiming Global Coherence in Semi-Autoregressive Diffusion
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