Low Gen-PPL in continuous diffusion LMs results from repetition caused by a 1D contractive attractor in self-conditioning feedback; ACE subtracts the direction to reduce repetition to human levels while preserving quality.
Breaking the Factorization Barrier in Diffusion Language Models
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cs.CL 2years
2026 2verdicts
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The paper introduces Uni-E, a unified energy for DLMs that accounts for model capacity, dependency and invariance, can be computed exactly, and corrects distribution shifts from dependency and invariance.
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Low Perplexity is Repetition: A One-Dimensional Self-Conditioning Attractor in Continuous Diffusion LMs
Low Gen-PPL in continuous diffusion LMs results from repetition caused by a 1D contractive attractor in self-conditioning feedback; ACE subtracts the direction to reduce repetition to human levels while preserving quality.
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Unified Energy for Invariant and Independent Decoding in Diffusion Language Models
The paper introduces Uni-E, a unified energy for DLMs that accounts for model capacity, dependency and invariance, can be computed exactly, and corrects distribution shifts from dependency and invariance.