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VLM as Policy: Common-Law Content Moderation Framework for Short Video Platform
Xingyu Lu, Tianke Zhang, Chang Meng +14
Exponentially growing short video platforms (SVPs) face significant challenges in moderating content detrimental to users' mental health, particularly for minors. The dissemination…
InstructEngine: Instruction-driven Text-to-Image Alignment
Xingyu Lu, Yuhang Hu, YiFan Zhang +9
Reinforcement Learning from Human/AI Feedback (RLHF/RLAIF) has been extensively utilized for preference alignment of text-to-image models. Existing methods face certain limitations…
Decoupling Contrastive Decoding: Robust Hallucination Mitigation in Multimodal Large Language Models
Wei Chen, Xin Yan, Bin Wen +4
Although multimodal large language models (MLLMs) exhibit remarkable reasoning capabilities on complex multimodal understanding tasks, they still suffer from the notorious hallucin…
TIME: Temporal-Sensitive Multi-Dimensional Instruction Tuning and Robust Benchmarking for Video-LLMs
Yunxiao Wang, Meng Liu, Wenqi Liu +7
Video large language models have achieved remarkable performance in tasks such as video question answering, however, their temporal understanding remains suboptimal. To address thi…
Exo2Ego: Exocentric Knowledge Guided MLLM for Egocentric Video Understanding
Haoyu Zhang, Qiaohui Chu, Meng Liu +3
AI personal assistants, deployed through robots or wearables, require embodied understanding to collaborate effectively with humans. However, current Multimodal Large Language Mode…
iMOVE: Instance-Motion-Aware Video Understanding
Jiaze Li, Yaya Shi, Zongyang Ma +7
Enhancing the fine-grained instance spatiotemporal motion perception capabilities of Video Large Language Models is crucial for improving their temporal and general video understan…
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Yi-Fan Zhang, Tao Yu, Haochen Tian +17
Despite notable advancements in Multimodal Large Language Models (MLLMs), most state-of-the-art models have not undergone thorough alignment with human preferences. This gap exists…
TaskGalaxy: Scaling Multi-modal Instruction Fine-tuning with Tens of Thousands Vision Task Types
Jiankang Chen, Tianke Zhang, Changyi Liu +8
Multimodal visual language models are gaining prominence in open-world applications, driven by advancements in model architectures, training techniques, and high-quality data. Howe…