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Hao Wu

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Preprint Oct 2026

Jag: Direct Box Prediction for Efficient Visual Grounding

Visual grounding combines image--language understanding with geometric prediction, yet autoregressive multimodal models often express a box as a coordinate sequence. Sequential decoding adds computation to the multimodal processing needed for localization. Adapting these representations to box geometry offers a route t...

Xiu-Yuan Zhu, Ke Lu, Hao Wu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

Across widely adopted grounding benchmarks and navigation benchmarks spanning multiple platforms, LLaDA-UI substantially outperforms Qwen2.5-VL-7B and surpasses Qwen3-VL-8B on four of six reported GUI benchmarks, establishing block-wise diffusion as a practical generative paradigm for multimodal GUI agents.

Zhangxuan Gu, Hao-Xin Chen, Qiujieli Qin et al. · 0 citations
Jul 2026

IoUPD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models

Experiments on standard referring-expression grounding benchmarks show consistent region-level improvements over strong coordinate-generating baselines, demonstrating that ground-truth boxes can provide useful privileged guidance beyond serving as coordinate labels.

Xiuyuan Zhu, Ke Lu, Hao Wu et al. · 0 citations
Preprint Aug 2026

Hi-Token: Hierarchical Coordinate Tokenization for Generative Visual Grounding

The results show that structured coordinate generation provides an effective approach to generative visual grounding and Hi-Token encodes each coordinate with axis-specific tokens for the hundreds, tens, and ones digits, which adds coarse-to-fine structure and increases token reuse while retaining the existing VLM arch...

Xiuyuan Zhu, Ke Lu, Kun Dong et al. · 0 citations

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