4 papers
Who You Are Matters: Bridging Topics and Social Roles via LLM-Enhanced Logical Recommendation
Qing Yu, Xiaobei Wang, Shuchang Liu +14
Recommender systems filter contents/items valuable to users by inferring preferences from user features and historical behaviors. Mainstream approaches follow the learning-to-rank…
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…
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…
EVLM: An Efficient Vision-Language Model for Visual Understanding
Kaibing Chen, Dong Shen, Hanwen Zhong +14
In the field of multi-modal language models, the majority of methods are built on an architecture similar to LLaVA. These models use a single-layer ViT feature as a visual prompt,…