8 papers
PushDualGen: Enabling LLMs to Generate Semantic IDs with Interpretable Copy for Industrial Push Recommendation
Manjia Lin, Da Li, Yan Wang +9
Push recommendation in KuaiShou proactively delivers personalized content to nearly one billion users to facilitate their engagement. Recently, generative recommendation has achiev…
Robust and Generalizable Safety Steering for Text-to-Image Diffusion Transformers
Zihao Xue, Yan Wang, Zhen Bi +7
Diffusion Transformers have become a powerful backbone for text-to-image generation, but their layered and cross-modal generation process makes safety control fundamentally differe…
Make LLM Learn to Synthesize from Streaming Experiences through Feedback
Zhenlin Hu, Yan Wang, Zhen Bi +7
Large language models (LLMs) have been widely adopted for synthetic data generation, significantly reducing annotation costs. However, most existing studies treat synthesis as a se…
Thinking as Compression: Your Reasoning Model is Secretly a Context Compressor
Guoxin Ma, Yibing Liu, Chengzhengxu Li +7
Context compression aims to shorten long context inputs with minimal information loss for LLM inference acceleration. While existing methods have shown promise, they typically rely…
Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses
Yan Wang, Ziyi Guo, Christopher McCarty
Survey research faces mounting structural challenges: declining response rates, sample bias, block-wise missingness among at-risk respondents, and AI-assisted fraudulent completion…
Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding
Da Li, Yuxiao Luo, Keping Bi +7
Multimodal Large Language Models advance multimodal representation learning by acquiring transferable semantic embeddings, thereby substantially enhancing performance across a rang…