4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.CV2026
OmniCap-IF: Benchmarking and Improving Instruction Following Abilities for Omni-Video Captioning
Jiahao Wang, An Ping, Yanghai Wang +13
While Omni-modal Large Language Models (OLLMs) have demonstrated impressive capabilities in jointly processing audio and visual streams, their ability to strictly adhere to complex…
cs.CV2026
Rethinking Genomic Modeling Through Optical Character Recognition
Hongxin Xiang, Pengsen Ma, Yunkang Cao +4
Recent genomic foundation models largely adopt large language model architectures that treat DNA as a one-dimensional token sequence. However, exhaustive sequential reading is stru…
cs.AI2026★ 4 cited
The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection
Wei Ai, Yilong Tan, Yuntao Shou +4
In recent years, the rapid evolution of large vision-language models (LVLMs) has driven a paradigm shift in multimodal fake news detection (MFND), transforming it from traditional…