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Shenghao Xie

7 accepted papers

2026

Motus: A Unified Latent Action World Model

CVPR 2026

While a general embodied agent must function as a unified system, current methods are built on isolated models for understanding, world modeling, and control. This fragmentation prevents unifying multimodal generative capabilities and hinders learning from large-scale, heterogeneous data. In this pa

Cited by 0SourcecodeScholar
2026

Nano3D: A Training-Free Approach for Efficient 3D Editing Without Masks

ICLR 2026poster

3D object editing is essential for interactive content creation in gaming, animation, and robotics, yet current approaches remain inefficient, inconsistent, and often fail to preserve unedited regions. Most methods rely on editing multi-view renderings followed by reconstruction, which introduces ar…

Cited by 0SourcecodeScholar
2026

Nearly Space-Optimal Graph and Hypergraph Sparsification in Insertion-Only Data Streams

ICLR 2026poster

We study the problem of graph and hypergraph sparsification in insertion-only data streams. The input is a hypergraph $H=(V, E, w)$ with $n$ nodes, $m$ hyperedges, and rank $r$, and the goal is to compute a hypergraph $\widehat{H}$ that preserves the energy of each vector $x \in \mathbb{R}^n$ in $H$…

Cited by 0SourceScholar
2025

Deterministic Sparse Fourier Transform for Continuous Signals with Frequency Gap

ICML 2025poster

The Fourier transform is a fundamental tool in computer science and signal processing. In particular, when the signal is sparse in the frequency domain---having only $k$ distinct frequencies---sparse Fourier transform (SFT) algorithms can recover the signal in a sublinear time (proportional to the s…

Cited by 0SourcePDFScholar
2025

ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding

NeurIPS 2025spotlight

Recently, the powerful text-to-image capabilities of GPT-4o have led to growing appreciation for native multimodal large language models. However, its multimodal capabilities remain confined to images and text. Yet beyond images, the ability to understand and generate 3D content is equally crucial.…

Cited by 0SourcecodeScholar
2024

FM-OV3D: Foundation Model-Based Cross-Modal Knowledge Blending for Open-Vocabulary 3D Detection

AAAI 2024technical

The superior performances of pre-trained foundation models in various visual tasks underscore their potential to enhance the 2D models' open-vocabulary ability. Existing methods explore analogous applications in the 3D space. However, most of them only center around knowledge extraction from singula…