6 citations · 12 across the 5 of their papers we have counts for
5 papers
Conversational Dueling Bandits in Generalized Linear Models
Shuhua Yang, Hui Yuan, Xiaoying Zhang +3
Conversational recommendation systems elicit user preferences by interacting with users to obtain their feedback on recommended commodities. Such systems utilize a multi-armed band…
Human-Instruction-Free LLM Self-Alignment with Limited Samples
Hongyi Guo, Yuanshun Yao, Wei Shen +4
Aligning large language models (LLMs) with human values is a vital task for LLM practitioners. Current alignment techniques have several limitations: (1) requiring a large amount o…
SGP-TOD: Building Task Bots Effortlessly via Schema-Guided LLM Prompting
Xiaoying Zhang, Baolin Peng, Kun Li +2
Building end-to-end task bots and maintaining their integration with new functionalities using minimal human efforts is a long-standing challenge in dialog research. Recently large…
Debiasing Recommendation by Learning Identifiable Latent Confounders
Qing Zhang, Xiaoying Zhang, Yang Liu +4
Recommendation systems aim to predict users' feedback on items not exposed to them. Confounding bias arises due to the presence of unmeasured variables (e.g., the socio-economic st…
Disentangled Representation for Diversified Recommendations
Xiaoying Zhang, Hongning Wang, Hang Li
Accuracy and diversity have long been considered to be two conflicting goals for recommendations. We point out, however, that as the diversity is typically measured by certain pre-…