mlsanityData to 7 Oct 2026

CaLR: Causal Latent Revision for Robust Diffusion Reasoning

arXiv 2609.20981 ↗First posted 17 Sep 2026cs.AIcited by 0

On the map: LLM reasoning → Diffusion reasoning and test-time scaling

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Abstract (arXiv)

Autoregressive (AR) models suffer from local greediness, while diffusion language models (DLMs) often lack the strict causal structure required for reasoning. To combine the advantages and overcome the drawbacks of the dual, we propose Causal Latent Revision (CaLR), a framework that reformulates reasoning as constrained latent optimization. By adopting a causal topology matrix (CTM) from an expert model and implicit differentiation, CaLR performs gradient-guided ``thought revision" to enforce logical consistency, enabling dynamic self-correction of intermediate steps during parallel generation. Empirically, CaLR achieves SOTA DLM performance on complex benchmarks, surpassing strong AR baselines and demonstrating superior robustness in constrained tasks like Sudoku.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Diffusion reasoning and test-time scaling, one of 17 directions in LLM reasoning. Builds on 33 of its 33 references that are in the map. First posted on arXiv 17 Sep 2026.

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33 of 33 references.

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Same direction, newest first

  1. 2024Beyond Autoregression: Discrete Diffusion for Complex Reasoning and Planning18 Oct

Other references · 32

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  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  7. 2025Qwen3 Technical Reportcited by 8,195
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  11. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  12. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,710
20 more
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  2. 2023GPQA: A Graduate-Level Google-Proof Q&A Benchmarkcited by 2,748
  3. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  4. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  5. 2025Large Language Diffusion Modelscited by 872
  6. 2024Simple and Effective Masked Diffusion Language Modelscited by 800
  7. 2023Discrete Diffusion Modeling by Estimating the Ratios of the Data Distributioncited by 712
  8. 2023Measuring Faithfulness in Chain-of-Thought Reasoningcited by 668
  9. 2025Dream 7B: Diffusion Large Language Modelscited by 515
  10. 2025SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Modelcited by 307
  11. 2025Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusionscited by 208
  12. 2025Survey on Evaluation of LLM-based Agentscited by 190
  13. 2022Score-based Continuous-time Discrete Diffusion Modelscited by 167
  14. 2025LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuningcited by 145
  15. 2025Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmaskingcited by 128
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  17. 2025A Survey on Diffusion Language Modelscited by 75
  18. 2025Discrete Diffusion in Large Language and Multimodal Models: A Surveycited by 61
  19. 2025Time Is a Feature: Exploiting Temporal Dynamics in Diffusion Language Modelscited by 33
  20. 2025When Safe Unimodal Inputs Collide: Optimizing Reasoning Chains for Cross-Modal Safety in Multimodal Large Language Modelscited by 3

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