On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators
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Updated
Aug 31, 2026 - Python
On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators
[Official Implementation] Acoustic Autoregressive Modeling 🔥
Generative Models for Real-World Sensor Time Series
Reproducibility study of Planning-Ahead Generative Retrieval (PAG), probing lexical planner robustness under query perturbations and cross-lingual evaluation. SIGIR 2026 Reproducibility Track.
How Chain-of-Thought Budgets Induce Overconfidence in LLMs. Investigating Calibration Drift Under Reasoning (CDUR), hypothesis lock-in mechanisms, and dynamic token budgeting via the CABStop optimal stopping algorithm.
Research code for the Dynamic Mixture-of-Experts in Visual Autoregressive Models paper.
Neural ODE Transformer in Julia, trained via adjoint sensitivity methods. Matched-architecture vs. discrete Transformer on Penn Treebank: 119.9 val perplexity vs 113.7 discrete. Single-seed result; discrete wins at this scale as expected, continuous-depth advantage expected to emerge at larger scale.
Exploring the architecture of the tech and its evolution that forms the backbone of the state-of-the-art NLP systems
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