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Hui Xiong

7 papers indexed

arxivcs.CV2026-07-21

CR-Refiner: An Object-Centric Optimal Transport Reranker for Edit-Conditioned 3D Scene Retrieval

Hao Wu, Jinjing Zhu, Nanyu Wu, Qianyi Cai, Heyi Lin, Hao Wang, et al.

Edit-conditioned 3D scene retrieval pairs a reference 3D room with a natural-language modification and retrieves rooms from a corpus that satisfy the edit. Three lines of prior work each fall short on this task. 2D composed image retrieval reasons over pixel-level edits and has n…

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arxivcs.CV2026-07-21

GATE-3D: Geometry-Aware Test-time Adaptive Reranking for Open-Set 3D Shape Retrieval

Hao Wu, Heyi Lin, Zilin Wang, Huizai Yao, Hao Wang, Hui Xiong

Large pretrained vision models have substantially improved appearance-based 3D shape retrieval, but they still confuse shapes that look similar while differing in geometry. Although geometry-aware features can reduce these errors, naive fusion of geometry and appearance may hurt…

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arxivcs.CVcs.RO2026-07-14

Just-In-Time Scene Graph Growth: Combating Perceptual Saturation in Long-Horizon Robotics

Yue Chang, Rufeng Chen, Yifan Tian, Dazhi Huang, Zhaofan Zhang, Yi Chen, et al.

While 3D Scene Graphs (3DSGs) provide crucial structured representations for embodied agents, conventional Ahead-of-Time, build-everything-then-filter pipelines conflict with the real-time, low-latency demands of edge platforms, inducing a perceptual saturation effect via severe…

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arxivcs.ROcs.AI2026-07-11

Source-Lifted Flow Matching for Intervenable Multimodal Imitation

He Zhang, Ying Sun, Pengteng Li, Ziyang Chen, Yiren Zhao, Ziyang Rao, et al.

Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity is largely passive: repeated sampling may yield diverse behaviors, but users cannot directly choose among valid continuations from…

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arxivcs.AIcs.CL2026-07-09

Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning

Lu Dai, Ziyang Rao, Yili Wang, Hanqing Wang, Hao Liu, Hui Xiong

Fine-tuning LLMs to inject new knowledge faces a critical challenge: LLMs can quickly memorize new facts, yet fail to use them for downstream reasoning tasks. We formalize this failure as the \textit{\textbf{Knowing--Using Gap}}, characterized by an accuracy gap and a temporal la…

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arxivcs.RO2026-07-04

LH-AVLN: A Benchmark for Long-Horizon Audio-Visual-Language Navigation

Rufeng Chen, Yue Chang, Zili Shao, Zhaofan Zhang, Li Chen, Hechang Chen, et al.

Embodied navigation is moving toward long-horizon missions, yet existing long-horizon benchmarks are largely acoustically silent, and audio-visual navigation tasks typically focus on a single goal. We introduce LH-AVLN, a benchmark for Long-Horizon Audio-Visual-Language Navigatio…

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arxivcs.LGcs.AI2026-07-04

Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution

Yazheng Liu, Xi Zhang, Sihong Xie, Hui Xiong

Temporal graphs are ubiquitous in real-world applications and Temporal Graph Networks (TGNs) have achieved superior predictive accuracy. Understanding which historical events drive model predictions can enhance trustworthiness of TGNs. Existing explanation methods overlook the me…

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