2 papers
cs.CL2024
Calibrating the Confidence of Large Language Models by Eliciting Fidelity
Mozhi Zhang, Mianqiu Huang, Rundong Shi +5
Large language models optimized with techniques like RLHF have achieved good alignment in being helpful and harmless. However, post-alignment, these language models often exhibit o…
cs.IR2024
Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework
Dongbo Xi, Zhen Chen, Yuexian Wang +4
Feed recommendation is currently the mainstream mode for many real-world applications (e.g., TikTok, Dianping), it is usually necessary to model and predict user interests in multi…