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20212026
most citedPanGu-: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

94 citations · 94 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

VideoResearcher: Self-Improving Tool Design for Long-Video Understanding

Dingqiang Ye, Dongdi Zhao, Kaishen Wang +11

Video agents have made substantial progress in long-video understanding. Yet effective video-agent systems require costly, time-consuming manual design and trial and error. Current…

cs.CV2026

Where to Look Matters: On-Policy Self-Distillation for Long-Video Understanding

Kaishen Wang, Dongdi Zhao, Yijun Liang +4

Vision-language models (VLMs) have made substantial progress in long-video understanding, with standard backbone models typically answering questions from frames sampled across the…

cs.CL2026

Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization

Kaishen Wang, Tong Zheng, Xuehao Cui +3

Large reasoning models (LRMs) improve language model capabilities by generating explicit thinking traces before final answers. In factuality-oriented question answering (QA), such…

cs.CV2026

Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention

Chaowen Yan, Kaishen Wang, Yong Wang +2

Oracle Bone Inscriptions (OBIs) recognition plays a crucial role in understanding ancient Chinese culture. However, accurately recognizing OBIs remains highly challenging due to th…

cs.CV2026

Unsafe by Reciprocity: How Generation-Understanding Coupling Undermines Safety in Unified Multimodal Models

Kaishen Wang, Heng Huang

Recent advances in Large Language Models (LLMs) and Text-to-Image (T2I) models have led to the emergence of Unified Multimodal Models (UMMs), where multimodal understanding and ima…

cs.CL2026

Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing

Tong Zheng, Chengsong Huang, Runpeng Dai +9

Parallel thinking has emerged as a promising paradigm for reasoning, yet it imposes significant computational burdens. Existing efficiency methods primarily rely on local, per-traj…