12 papers
CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning
Penghui Yang, Long Xing, Xiaoyi Dong +10
Image and video captioning are fundamental tasks that bridge the visual and linguistic domains, playing a critical role in pre-training Large Vision-Language Models (LVLMs). Curren…
Harnessing Streaming Video in the Wild
Dingyu Yao, Shuhuan Gu, Qingyi Si +8
Vision-Language Models (VLMs) are increasingly required to process unbounded video streams in applications such as video-call assistants, live commentary, and embodied robots. An i…
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…
Light-WAM: Efficient World Action Models with State-Fusion Action Decoding
Ziang Li, Dongzhou Cheng, Yibin Wang +5
World Action Models (WAMs) extend robot policy learning by incorporating future prediction as an additional training objective, encouraging the policy to encode task-relevant tempo…
AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO
Jiazi Bu, Pengyang Ling, Yujie Zhou +8
Group Relative Policy Optimization (GRPO) has demonstrated remarkable success in aligning text-to-image (T2I) flow models with human preferences. However, we have identified that t…
LoMo: Local Modality Substitution for Deeper Vision-Language Fusion
Feng Han, Zhixiong Zhang, Zheming Liang +2
Vision-Language Models (VLMs) have achieved substantial progress across a wide range of understanding and reasoning tasks, driven by large-scale image-text training aimed at multim…