120 citations · 321 across the 32 of their papers we have counts for
33 papers
SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields
Youkang Kong, Yang Liu, Yue Dong +2
3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. Existing quad-remeshing techniq…
The Vertical Challenge of Low-Altitude Economy: Why We Need a Unified Height System?
Shuaichen Yan, Xiao Hu, Jiayang Sun +5
The explosive growth of the low-altitude economy, driven by eVTOLs and UAVs, demands a unified digital infrastructure to ensure safety and scalability. However, the current aviatio…
Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters
Ailin Huang, Ang Li, Aobo Kong +213
We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most wh…
SWE-AGI: Benchmarking Specification-Driven Software Construction with MoonBit in the Era of Autonomous Agents
Zhirui Zhang, Hongbo Zhang, Haoxiang Fei +11
Although large language models (LLMs) have demonstrated impressive coding capabilities, their ability to autonomously build production-scale software from explicit specifications r…
PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning
Jingcheng Hu, Yinmin Zhang, Shijie Shang +17
We introduce Parallel Coordinated Reasoning (PaCoRe), a training-and-inference framework designed to overcome a central limitation of contemporary language models: their inability…
Follow-Your-Emoji-Faster: Towards Efficient, Fine-Controllable, and Expressive Freestyle Portrait Animation
Yue Ma, Zexuan Yan, Hongyu Liu +11
We present Follow-Your-Emoji-Faster, an efficient diffusion-based framework for freestyle portrait animation driven by facial landmarks. The main challenges in this task are preser…
LazyDrag: Enabling Stable Drag-Based Editing on Multi-Modal Diffusion Transformers via Explicit Correspondence
Zixin Yin, Xili Dai, Duomin Wang +4
The reliance on implicit point matching via attention has become a core bottleneck in drag-based editing, resulting in a fundamental compromise on weakened inversion strength and c…
Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer
Zixin Yin, Xili Dai, Ling-Hao Chen +7
Text-guided color editing in images and videos is a fundamental yet unsolved problem, requiring fine-grained manipulation of color attributes, including albedo, light source color,…
Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding
StepFun, :, Bin Wang +195
Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…
Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model
Ailin Huang, Bingxin Li, Bruce Wang +73
Large Audio-Language Models (LALMs) have significantly advanced intelligent human-computer interaction, yet their reliance on text-based outputs limits their ability to generate na…
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Jingcheng Hu, Yinmin Zhang, Qi Han +3
We introduce Open-Reasoner-Zero, the first open source implementation of large-scale reasoning-oriented RL training on the base model focusing on scalability, simplicity and access…
Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction
Ailin Huang, Boyong Wu, Bruce Wang +142
Real-time speech interaction, serving as a fundamental interface for human-machine collaboration, holds immense potential. However, current open-source models face limitations such…
Taming Teacher Forcing for Masked Autoregressive Video Generation
Deyu Zhou, Quan Sun, Yuang Peng +8
We introduce MAGI, a hybrid video generation framework that combines masked modeling for intra-frame generation with causal modeling for next-frame generation. Our key innovation,…
Large Investment Model
Jian Guo, Heung-Yeung Shum
Traditional quantitative investment research is encountering diminishing returns alongside rising labor and time costs. To overcome these challenges, we introduce the Large Investm…
Follow-Your-Emoji: Fine-Controllable and Expressive Freestyle Portrait Animation
Yue Ma, Hongyu Liu, Hongfa Wang +8
We present Follow-Your-Emoji, a diffusion-based framework for portrait animation, which animates a reference portrait with target landmark sequences. The main challenge of portrait…
Follow-Your-Click: Open-domain Regional Image Animation via Short Prompts
Yue Ma, Yingqing He, Hongfa Wang +8
Despite recent advances in image-to-video generation, better controllability and local animation are less explored. Most existing image-to-video methods are not locally aware and t…
HumanTOMATO: Text-aligned Whole-body Motion Generation
Shunlin Lu, Ling-Hao Chen, Ailing Zeng +4
This work targets a novel text-driven whole-body motion generation task, which takes a given textual description as input and aims at generating high-quality, diverse, and coherent…
TOSS:High-quality Text-guided Novel View Synthesis from a Single Image
Yukai Shi, Jianan Wang, He Cao +7
In this paper, we present TOSS, which introduces text to the task of novel view synthesis (NVS) from just a single RGB image. While Zero-1-to-3 has demonstrated impressive zero-sho…
Reinforced Disentanglement for Face Swapping without Skip Connection
Xiaohang Ren, Xingyu Chen, Pengfei Yao +2
The SOTA face swap models still suffer the problem of either target identity (i.e., shape) being leaked or the target non-identity attributes (i.e., background, hair) failing to be…
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang +6
Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep an…
Locally Attentional SDF Diffusion for Controllable 3D Shape Generation
Xin-Yang Zheng, Hao Pan, Peng-Shuai Wang +3
Although the recent rapid evolution of 3D generative neural networks greatly improves 3D shape generation, it is still not convenient for ordinary users to create 3D shapes and con…
Closed-Loop Transcription via Convolutional Sparse Coding
Xili Dai, Ke Chen, Shengbang Tong +9
Autoencoding has achieved great empirical success as a framework for learning generative models for natural images. Autoencoders often use generic deep networks as the encoder or d…
Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence
Jian Guo, Saizhuo Wang, Lionel M. Ni +1
Quantitative investment (``quant'') is an interdisciplinary field combining financial engineering, computer science, mathematics, statistics, etc. Quant has become one of the mains…
Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesis
Duomin Wang, Yu Deng, Zixin Yin +2
We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression.…