arXiv AI
Flow Reasoning Models: Turning Flows Into Efficient Recurrent Reasoners
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Flow Reasoning Models: Scaling Reasoning Through Iterative Self-Refinement
arXiv:2606. 29150v1 Announce Type: new Abstract: Discrete flow models have recently shown promising performance on few-step text generation; however, when naively applied to structured reasoning tasks such as Sudoku and Zebra puzzles, they converge confidently to incorrect answers (solving only $\sim$36% of Sudoku puzzles).
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Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
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What Survives When You Compress a Recursive Reasoner for the Edge?
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MetaState: Persistent Working Memory Enhances Reasoning in Discrete Diffusion Language Models
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Can We Break LLMs Out of Self-Loops? Fine-Grained Reasoning Control with Activation Steering
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