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James Kwok

ICLR 2026×3ACL 2026×2AAAI 2026CVPR 2026多模态对齐与偏好效率与系统安全推理
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合作网络9
0 一作 · 7 篇 · ICLR 2026 / ACL 2026 / AAAI 2026 / CVPR 2026

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2026 顶会论文

7
作者位次 #3/4ICLR 2026Poster· Deep Learning / Robustness

Discrete Latent Features Ablate Adversarial Attack: A Robust Prompt Tuning Framework for VLMs

YANG CHEN · Yanbin Wei · James Kwok · Yu Zhang

安全多模态OpenReview
作者位次 #3/3ACL 2026Findings· Findings of ACL

Diffusion with Truncated Blocks: Fast and High-Quality Text Generation using Truncated Block Generation

Yuyan Zhou · Weiyu Chen · James Kwok

摘要

Diffusion-based Large Language Models (dLLMs) are emerging as a powerful alternative to traditional autoregressive models. These models learn to generate text by iteratively denoising masked sequences. In this work, we identify a critical problem in dLLMs: the model’s attention is wastefully expe...

效率与系统检索与知识OpenReview 项目页
作者位次 #7/8ACL 2026Findings· Findings of ACL

Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework

Yibo Yan · Mingdong Ou · Yi Cao · Xin Zou · Jiahao Huo · Shuliang Liu · James Kwok · Xuming Hu

摘要

Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current multimodal retrieval applications. The state-of-the-art multi-vector paradigm excels in performance but suffers from prohibitive overhead, a problem...

效率与系统多模态数据与预训练OpenReview 项目页

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