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20172026
most citedDomain Enhanced Arbitrary Image Style Transfer via Contrastive Learning

209 citations

Showing 2025Show all

15 papers · 1 filter

cs.CV2025

VDC-Agent: When Video Detailed Captioners Evolve Themselves via Agentic Self-Reflection

Qiang Wang, Xinyuan Gao, Yuhang He +5

Existing Video Detailed Captioning (VDC) methods predominantly rely on costly human annotations or distillation from powerful proprietary models, creating a dependency on external…

cs.CV2025★ 1 cited

StreamingCoT: A Dataset for Temporal Dynamics and Multimodal Chain-of-Thought Reasoning in Streaming VideoQA

Yuhang Hu, Zhenyu Yang, Shihan Wang +5

The rapid growth of streaming video applications demands multimodal models with enhanced capabilities for temporal dynamics understanding and complex reasoning. However, current Vi…

cs.IR2025

Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce

Zhiding Liu, Ben Chen, Mingyue Cheng +6

Search-based recommendation is one of the most critical application scenarios in e-commerce platforms. Users' complex search contexts--such as spatiotemporal factors, historical in…

cs.IR2025

GRank: Towards Target-Aware and Streamlined Industrial Retrieval with a Generate-Rank Framework

Yijia Sun, Shanshan Huang, Zhiyuan Guan +4

Industrial-scale recommender systems rely on a cascade pipeline in which the retrieval stage must return a high-recall candidate set from billions of items under tight latency. Exi…

cs.IR2025

MPFormer: Adaptive Framework for Industrial Multi-Task Personalized Sequential Retriever

Yijia Sun, Shanshan Huang, Linxiao Che +4

Modern industrial recommendation systems encounter a core challenge of multi-stage optimization misalignment: a significant semantic gap exists between the multi-objective optimiza…

cs.LG2025★ 1 cited

Expert-Guided Diffusion Planner for Auto-Bidding

Yunshan Peng, Wenzheng Shu, Jiahao Sun +6

Auto-bidding is widely used in advertising systems, serving a diverse range of advertisers. Generative bidding is increasingly gaining traction due to its strong planning capabilit…