1 citations · 1 across the 15 of their papers we have counts for
15 papers
The Field Knows: Cross-Dimensional Geometry from Navigation to Black Holes
Chenghao Xu
We introduce a continuous metric field framework trained by a single causal contrastive loss. The framework encodes a scene into coefficients of a fixed symmetric matrix basis, ass…
Semantic Evidence Regulation via Relational Bias for Zero-Shot Object Navigation
Weitao An, Chenghao Xu, Xu Yang +1
Object navigation requires an embodied agent to locate a target object in an unknown environment through visual observations. Existing zero-shot methods typically leverage open-voc…
Space Is Intelligence: Neural Semigroup Superposition for Riemannian Metric Generation
Chenghao Xu
Traditional approaches place intelligence in the agent, whether as a learned policy or a search procedure. We instead place intelligence in the space itself: a scene induces a Riem…
Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation
Yujia Cai, Boxuan Li, Chenghao Xu +1
Query-based image retrieval (QBIR) requires retrieving relevant images given diverse and often stylistically heterogeneous queries, such as sketches, artworks, or low-resolution pr…
Beyond Global Alignment: Fine-Grained Motion-Language Retrieval via Pyramidal Shapley-Taylor Learning
Hanmo Chen, Guangtao Lyu, Chenghao Xu +3
As a foundational task in human-centric cross-modal intelligence, motion-language retrieval aims to bridge the semantic gap between natural language and human motion, enabling intu…
Past- and Future-Informed KV Cache Policy with Salience Estimation in Autoregressive Video Diffusion
Hanmo Chen, Chenghao Xu, Xu Yang +2
Video generation is pivotal to digital media creation, and recent advances in autoregressive video generation have markedly enhanced the efficiency of real-time video synthesis. Ho…
Your AI-Generated Image Detector Can Secretly Achieve SOTA Accuracy, If Calibrated
Muli Yang, Gabriel James Goenawan, Henan Wang +7
Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit systematic bias at test time, frequently misclassifying fake images as real. We hypo…
Towards Interpretable Hallucination Analysis and Mitigation in LVLMs via Contrastive Neuron Steering
Guangtao Lyu, Xinyi Cheng, Qi Liu +5
LVLMs achieve remarkable multimodal understanding and generation but remain susceptible to hallucinations. Existing mitigation methods predominantly focus on output-level adjustmen…
DSCD-Nav: Dual-Stance Cooperative Debate for Object Navigation
Weitao An, Qi Liu, Chenghao Xu +4
Adaptive navigation in unfamiliar indoor environments is crucial for household service robots. Despite advances in zero-shot perception and reasoning from vision-language models, e…
Towards Arbitrary Motion Completing via Hierarchical Continuous Representation
Chenghao Xu, Guangtao Lyu, Qi Liu +3
Physical motions are inherently continuous, and higher camera frame rates typically contribute to improved smoothness and temporal coherence. For the first time, we explore continu…
A Turn Toward Better Alignment: Few-Shot Generative Adaptation with Equivariant Feature Rotation
Chenghao Xu, Qi Liu, Jiexi Yan +2
Few-shot image generation aims to effectively adapt a source generative model to a target domain using very few training images. Most existing approaches introduce consistency cons…
Revealing Perception and Generation Dynamics in LVLMs: Mitigating Hallucinations via Validated Dominance Correction
Guangtao Lyu, Xinyi Cheng, Chenghao Xu +7
Large Vision-Language Models (LVLMs) have shown remarkable capabilities, yet hallucinations remain a persistent challenge. This work presents a systematic analysis of the internal…
Tempo as the Stable Cue: Hierarchical Mixture of Tempo and Beat Experts for Music to 3D Dance Generation
Guangtao Lyu, Chenghao Xu, Qi Liu +4
Music to 3D dance generation aims to synthesize realistic and rhythmically synchronized human dance from music. While existing methods often rely on additional genre labels to furt…
AStF: Motion Style Transfer via Adaptive Statistics Fusor
Hanmo Chen, Chenghao Xu, Jiexi Yan +1
Human motion style transfer allows characters to appear less rigidity and more realism with specific style. Traditional arbitrary image style transfer typically process mean and va…
Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space
Xiang Zhang, Kun Wei, Xu Yang +3
As Large Language Models (LLMs) become increasingly prevalent, their security vulnerabilities have already drawn attention. Machine unlearning is introduced to seek to mitigate the…