#decoding-optimization News & Analysis

2 articles tagged with #decoding-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 237/10

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Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models

Researchers introduce Self-Aware Scheduling (SAS), a method that learns optimal token unmasking orders in masked diffusion language models through policy optimization. The approach significantly improves generation quality on reasoning tasks, achieving 91.8% accuracy on Sudoku (up from 82%) and boosting mathematical reasoning performance by 12 percentage points on GSM8K.

AIBullisharXiv – CS AI · Apr 157/10

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Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation

Researchers introduce Decoding by Perturbation (DeP), a training-free method that reduces hallucinations in multimodal large language models by applying controlled textual perturbations during decoding. The approach addresses the core issue where language priors override visual evidence, achieving improvements across multiple benchmarks without requiring model retraining or visual manipulation.