7 citations · 8 across the 13 of their papers we have counts for
14 papers
Let the Library Speak: Self-Advertised Method Selection for Formal Proving
Xiaopeng Yuan, Suijin Wang, Yanli Wang +5
LLM-based formal provers can retrieve relevant lemmas and prior proofs, but relevance alone does not say whether a mathematical method can be used on the current theorem. A method…
STEVE: Stabilizing Textual Gradient-Based Prompt Optimization via Error-Driven Refinement and Regularized Verification
Yifan Xu, Yixuan Li, Xinzhuo Li +4
Textual-gradient methods automate prompt optimization through natural-language feedback, but their iterative updates can be unstable. We identify two sources of this instability: n…
Closing the Loop on Latent Reasoning via Test-Time Reconstruction
Xiaopeng Yuan, Haibo Jin, Ye Yu +4
Recent work moves intermediate reasoning from natural-language traces into latent or cache-level representations to reduce token overhead and avoid a discrete communication bottlen…
SSD: Spatially Speculative Decoding Accelerates Autoregressive Image Generation
Shilong Xiang, Zirui Zhang, Lijun Yu +1
Autoregressive image models treat images as 1D token sequences, inheriting the next-token factorization of language models. This flattening discards a useful property of images: vi…
Archon: A Unified Multimodal Model for Holistic Digital Human Generation
Chong Bao, Shichen Liu, Lijun Yu +9
Digital humans are fundamental to immersive interaction, yet creating a unified model for holistic modalities, including text, audio, motion, and visual content, remains an open ch…
Cubic Discrete Diffusion: Discrete Visual Generation on High-Dimensional Representation Tokens
Yuqing Wang, Chuofan Ma, Zhijie Lin +7
Visual generation with discrete tokens has gained significant attention as it enables a unified token prediction paradigm shared with language models, promising seamless multimodal…
Rethinking Generative Image Pretraining: How Far Are We From Scaling Up Next-Pixel Prediction?
Xinchen Yan, Chen Liang, Lijun Yu +3
This paper investigates the scaling properties of autoregressive next-pixel prediction, a simple, end-to-end yet under-explored framework for unified vision models. Starting with i…
UISim: An Interactive Image-Based UI Simulator for Dynamic Mobile Environments
Jiannan Xiang, Yun Zhu, Lei Shu +6
Developing and testing user interfaces (UIs) and training AI agents to interact with them are challenging due to the dynamic and diverse nature of real-world mobile environments. E…
Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making
Xiaopeng Yuan, Xingjian Zhang, Ke Xu +5
Large language models (LLMs) are increasingly used for tasks that require complex reasoning. Most benchmarks focus on final outcomes but overlook the intermediate reasoning steps -…
YuE: Scaling Open Foundation Models for Long-Form Music Generation
Ruibin Yuan, Hanfeng Lin, Shuyue Guo +55
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the…
Language-Guided Image Tokenization for Generation
Kaiwen Zha, Lijun Yu, Alireza Fathi +4
Image tokenization, the process of transforming raw image pixels into a compact low-dimensional latent representation, has proven crucial for scalable and efficient image generatio…
MaskBit: Embedding-free Image Generation via Bit Tokens
Mark Weber, Lijun Yu, Qihang Yu +4
Masked transformer models for class-conditional image generation have become a compelling alternative to diffusion models. Typically comprising two stages - an initial VQGAN model…
Unified Discrete Diffusion for Categorical Data
Lingxiao Zhao, Xueying Ding, Lijun Yu +1
Discrete diffusion models have seen a surge of attention with applications on naturally discrete data such as language and graphs. Although discrete-time discrete diffusion has bee…
Score-based Continuous-time Discrete Diffusion Models
Haoran Sun, Lijun Yu, Bo Dai +2
Score-based modeling through stochastic differential equations (SDEs) has provided a new perspective on diffusion models, and demonstrated superior performance on continuous data.…