2 citations · 5 across the 16 of their papers we have counts for
16 papers
Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation
Jintao Zhang, Kai Jiang, Jintao Chen +32
We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. Moreover, we explore the…
TurboT2VA: Fast Large-Scale Text-to-Video-Audio Generation via Score-Regularized Consistency Distillation
Xiaoda Yang, Yuxiang Liu, Kaiwen Zheng +12
Joint text-to-video-audio generation produces synchronized visual and acoustic content, but the long sampling trajectories and heterogeneous multimodal computation of large models…
Vidu S1: A Real-Time Interactive Video Generation Model
Jintao Zhang, Kai Jiang, Jintao Chen +24
We introduce Vidu S1, a real-time interactive video generation model supporting voice control of digital characters. Users can control video generation content at any moment throug…
minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models
Min Zhao, Hongzhou Zhu, Bokai Yan +13
Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive video world models remains…
NFT: Bridging Supervised Learning and Reinforcement Learning in Math Reasoning
Huayu Chen, Kaiwen Zheng, Qinsheng Zhang +8
Reinforcement Learning (RL) has played a central role in the recent surge of LLMs' math abilities by enabling self-improvement through binary verifier signals. In contrast, Supervi…
DiffGAP: A Lightweight Diffusion Module in Contrastive Space for Bridging Cross-Model Gap
Shentong Mo, Zehua Chen, Fan Bao +1
Recent works in cross-modal understanding and generation, notably through models like CLAP (Contrastive Language-Audio Pretraining) and CAVP (Contrastive Audio-Visual Pretraining),…
Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
Kaiwen Zheng, Yongxin Chen, Huayu Chen +4
While likelihood-based generative models, particularly diffusion and autoregressive models, have achieved remarkable fidelity in visual generation, the maximum likelihood estimatio…
Elucidating the Preconditioning in Consistency Distillation
Kaiwen Zheng, Guande He, Jianfei Chen +2
Consistency distillation is a prevalent way for accelerating diffusion models adopted in consistency (trajectory) models, in which a student model is trained to traverse backward o…
Bridge-SR: Schrödinger Bridge for Efficient SR
Chang Li, Zehua Chen, Fan Bao +1
Speech super-resolution (SR), which generates a waveform at a higher sampling rate from its low-resolution version, is a long-standing critical task in speech restoration. Previous…
Consistency Diffusion Bridge Models
Guande He, Kaiwen Zheng, Jianfei Chen +2
Diffusion models (DMs) have become the dominant paradigm of generative modeling in a variety of domains by learning stochastic processes from noise to data. Recently, diffusion den…
Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
Kaiwen Zheng, Yongxin Chen, Hanzi Mao +3
Masked diffusion models (MDMs) have emerged as a popular research topic for generative modeling of discrete data, thanks to their superior performance over other discrete diffusion…
Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models
Fan Bao, Chendong Xiang, Gang Yue +7
We introduce Vidu, a high-performance text-to-video generator that is capable of producing 1080p videos up to 16 seconds in a single generation. Vidu is a diffusion model with U-Vi…
Diffusion Bridge Implicit Models
Kaiwen Zheng, Guande He, Jianfei Chen +2
Denoising diffusion bridge models (DDBMs) are a powerful variant of diffusion models for interpolating between two arbitrary paired distributions given as endpoints. Despite their…
Noise Contrastive Alignment of Language Models with Explicit Rewards
Huayu Chen, Guande He, Lifan Yuan +3
User intentions are typically formalized as evaluation rewards to be maximized when fine-tuning language models (LMs). Existing alignment methods, such as Direct Preference Optimiz…
Schrodinger Bridges Beat Diffusion Models on Text-to-Speech Synthesis
Zehua Chen, Guande He, Kaiwen Zheng +2
In text-to-speech (TTS) synthesis, diffusion models have achieved promising generation quality. However, because of the pre-defined data-to-noise diffusion process, their prior dis…
Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting
Guande He, Peng Cui, Jianfei Chen +2
Despite the significant progress made in practical applications of aligned language models (LMs), they tend to be overconfident in output answers compared to the corresponding pre-…