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20232026
most citedLLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation

6 citations · 13 across the 9 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.LG2024★ 3 cited

PageRank Bandits for Link Prediction

Yikun Ban, Jiaru Zou, Zihao Li +5

Link prediction is a critical problem in graph learning with broad applications such as recommender systems and knowledge graph completion. Numerous research efforts have been dire…

cs.LG2024★ 6 cited

LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation

Xinrui He, Yikun Ban, Jiaru Zou +3

Missing data imputation is a critical challenge in various domains, such as healthcare and finance, where data completeness is vital for accurate analysis. Large language models (L…

cs.LG2024

Meta Clustering of Neural Bandits

Yikun Ban, Yunzhe Qi, Tianxin Wei +2

The contextual bandit has been identified as a powerful framework to formulate the recommendation process as a sequential decision-making process, where each item is regarded as an…

cs.LG2024★ 1 cited

Neural Active Learning Beyond Bandits

Yikun Ban, Ishika Agarwal, Ziwei Wu +4

We study both stream-based and pool-based active learning with neural network approximations. A recent line of works proposed bandit-based approaches that transformed active learni…

cs.IR2024★ 2 cited

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

Tianxin Wei, Bowen Jin, Ruirui Li +8

Developing a universal model that can effectively harness heterogeneous resources and respond to a wide range of personalized needs has been a longstanding community aspiration. Ou…