1 citations · 1 across the 7 of their papers we have counts for
8 papers
Improving Few-Step Language Flows with Untied Self-Conditioning
Bocheng Li, Linli Xu
Flow-matching language models refine all token positions in parallel and can trade sampling steps for latency, yet generation quality still degrades sharply with few sampling steps…
Unifying Continuous and Discrete Text Diffusion with Non-simultaneous Diffusion Processes
Bocheng Li, Zhujin Gao, Linli Xu
Diffusion models have emerged as a promising approach for text generation, with recent works falling into two main categories: discrete and continuous diffusion models. Discrete di…
Addressing Representation Collapse in Vector Quantized Models with One Linear Layer
Yongxin Zhu, Bocheng Li, Yifei Xin +2
Vector Quantization (VQ) is essential for discretizing continuous representations in unsupervised learning but suffers from representation collapse, causing low codebook utilizatio…
Stabilize the Latent Space for Image Autoregressive Modeling: A Unified Perspective
Yongxin Zhu, Bocheng Li, Hang Zhang +3
Latent-based image generative models, such as Latent Diffusion Models (LDMs) and Mask Image Models (MIMs), have achieved notable success in image generation tasks. These models typ…
Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction
Haoqiu Yan, Yongxin Zhu, Kai Zheng +4
Large Language Model (LLM)-enhanced agents become increasingly prevalent in Human-AI communication, offering vast potential from entertainment to professional domains. However, cur…
Generative Pre-trained Speech Language Model with Efficient Hierarchical Transformer
Yongxin Zhu, Dan Su, Liqiang He +2
While recent advancements in speech language models have achieved significant progress, they face remarkable challenges in modeling the long acoustic sequences of neural audio code…
HRVDA: High-Resolution Visual Document Assistant
Chaohu Liu, Kun Yin, Haoyu Cao +6
Leveraging vast training data, multimodal large language models (MLLMs) have demonstrated formidable general visual comprehension capabilities and achieved remarkable performance a…
DiffS2UT: A Semantic Preserving Diffusion Model for Textless Direct Speech-to-Speech Translation
Yongxin Zhu, Zhujin Gao, Xinyuan Zhou +2
While Diffusion Generative Models have achieved great success on image generation tasks, how to efficiently and effectively incorporate them into speech generation especially trans…