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20242026
most citedGradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond

1 citations · 1 across the 11 of their papers we have counts for

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cs.CL2026

Rethinking the Generation Order of Block Diffusion Language Models

Kai Syun Hou, James Kwok

Diffusion language models enable flexible arbitrary-order generation, but existing sampling methods are mostly designed for early masked diffusion models (MDMs). In this work, we s…

cs.CL2026

Dynamic Chunking for Diffusion Language Models

Yichen Zhu, Xiaoming Shi, Peng Zhao +3

Block discrete diffusion language models factorize a sequence autoregressively over fixed-size positional blocks, decoupling within-block parallel denoising from across-block condi…

cs.CL2026

Attention-Based Sampler for Diffusion Language Models

Yuyan Zhou, Kai Syun Hou, Weiyu Chen +1

Auto-regressive models (ARMs) have established a dominant paradigm in language modeling. However, their strictly sequential sampling paradigm imposes fundamental constraints on bot…

cs.CL2026

Beyond the Grid: Layout-Informed Multi-Vector Retrieval with Parsed Visual Document Representations

Yibo Yan, Mingdong Ou, Yi Cao +6

Harnessing the full potential of visually-rich documents requires retrieval systems that understand not just text, but intricate layouts, a core challenge in Visual Document Retrie…

cs.CL2026

Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval

Yibo Yan, Jiahao Huo, Guanbo Feng +12

With the rapid proliferation of multimodal information, Visual Document Retrieval (VDR) has emerged as a critical frontier in bridging the gap between unstructured visually rich da…

cs.CL2026

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

Yibo Yan, Mingdong Ou, Yi Cao +5

Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current multimodal retrieval applicatio…