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NeurIPS 2026The Chinese University of Hong KShanghai Jiaotongnational university of singaore,Advanced Machine IntelligenceByteDance Inc.Autoregressive generation

BitDance: Scaling Autoregressive Generative Models with Binary Tokens

BitDance is an autoregressive image generator that predicts binary visual tokens via a diffusion head and next-patch decoding, achieving state-of-the-art FID with far fewer parameters and much faster inference.

Yuang Ai, Jiaming Han, Shaobin Zhuang, Weijia Mao and 7 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 46 on Hugging Face · Code ★ 485

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5
86%Must read
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NeurIPS 2026Carnegie MellonTikTokMorpheus AICMU, Carnegie MellonUniversity at Buffalo, SUNYVideo generation

MonarchRT: Efficient Attention for Real-Time Video Generation

Monarch-RT factorizes video diffusion attention via Monarch matrices to reach 95% sparsity without quality loss, enabling 16 FPS real-time generation on one GPU with 1.4-11.8x kernel speedups.

Krish Agarwal, Zhuoming Chen, cheng Luo, Yongqi Chen and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 2/5
78%Highly rated
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NeurIPS 2026Carnegie MellonNVIDIATikTokFederated learning

Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning

FedRevive revives stale asynchronous federated updates via server-side data-free knowledge distillation, accelerating training by 38.4% and boosting accuracy by 16.5%.

Baris Askin, Holger Roth, Zhenyu Sun, Carlee Joe-Wong and 2 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
78%Highly rated
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NeurIPS 2026The University of SydneyByteDance Inc.TikTokU SydneyShanghai JiaotongVideo-language models

From Failure Taxonomy to Intervention: A Diagnostic Methodology for Industry-Scale AVLM in Video and Live-Streaming Platform Moderation

A diagnostic taxonomy maps AVLM failure signatures to targeted development interventions, enabling traceable industry-scale video moderation system improvements.

Shuchang Ye, Jinqiang Yu, Zhujun Xiao, Yajing Kong and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5