7 papers
Efficient LLM-based Advertising via Model Compression and Parallel Verification
Wenxin Dong, Chang Gao, Guanghui Yu +9
Large language models (LLMs) have shown remarkable potential in advertising scenarios such as ad creative generation and targeted advertising. However, deploying LLMs in real-time…
Ada-MK: Adaptive MegaKernel Optimization via Automated DAG-based Search for LLM Inference
Wenxin Dong, Mingqing Hu, Guanghui Yu +7
When large language models (LLMs) serve real-time inference in commercial online advertising systems, end-to-end latency must be strictly bounded to the millisecond range. Yet ever…
LASAR: Latent Adaptive Semantic Aligned Reasoning for Generative Recommendation
Yiwen Chen, Fuwei Zhang, Zehao Chen +8
Large Language Models (LLMs) have demonstrated powerful reasoning capabilities through Chain-of-Thought (CoT) in various tasks, yet the inefficiency of token-by-token generation hi…
Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification
Shuang Li, Jiaxu Leng, Changjiang Kuang +3
VVI-ReID is a critical technique for all-day surveillance, where temporal information provides additional cues beyond static images. However, existing approaches rely heavily on fu…
RELATE: A Reinforcement Learning-Enhanced LLM Framework for Advertising Text Generation
Jinfang Wang, Jiajie Liu, Jianwei Wu +8
In online advertising, advertising text plays a critical role in attracting user engagement and driving advertiser value. Existing industrial systems typically follow a two-stage p…
UniGlyph: Unified Segmentation-Conditioned Diffusion for Precise Visual Text Synthesis
Yuanrui Wang, Cong Han, Yafei Li +8
Text-to-image generation has greatly advanced content creation, yet accurately rendering visual text remains a key challenge due to blurred glyphs, semantic drift, and limited styl…