4 papers
Orthogonal Low-rank Adaptation in Lie Groups for Continual Learning of Large Language Models
Kefan Cao, Shuaicheng Wu
Large language models (LLMs) suffer from catastrophic forgetting in sequential multi-task learning. Existing parameter regularization methods (e.g., O-LoRA, N-LoRA) mitigate interf…
HT-GNN: Hyper-Temporal Graph Neural Network for Customer Lifetime Value Prediction in Baidu Ads
Xiaohui Zhao, Xinjian Zhao, Jiahui Zhang +3
Lifetime value (LTV) prediction is crucial for news feed advertising, enabling platforms to optimize bidding and budget allocation for long-term revenue growth. However, it faces t…
GOT4Rec: Graph of Thoughts for Sequential Recommendation
Zewen Long, Liang Wang, Shu Wu +1
With their vast open-world knowledge and reasoning abilities, large language models (LLMs) have become a promising tool for sequential recommendation. Researchers have explored var…
Playing Language Game with LLMs Leads to Jailbreaking
Yu Peng, Zewen Long, Fangming Dong +3
The advent of large language models (LLMs) has spurred the development of numerous jailbreak techniques aimed at circumventing their security defenses against malicious attacks. An…